From d8ddc756820c5fd42ea10da219edc11af1552c0a Mon Sep 17 00:00:00 2001
From: Philipp Schaad <schaad.phil@gmail.com>
Date: Tue, 29 Oct 2024 16:56:41 +0100
Subject: [PATCH 01/33] Warn on potential data races (#1712)

Re-implement changes made by @luca-patrignani in #1541, see that PR for
more information.

Author: @luca-patrignani
---
 dace/config_schema.yml                        |   7 +
 dace/sdfg/validation.py                       |  51 ++-
 .../sdfg/warn_on_potential_data_race_test.py  | 316 ++++++++++++++++++
 3 files changed, 367 insertions(+), 7 deletions(-)
 create mode 100644 tests/sdfg/warn_on_potential_data_race_test.py

diff --git a/dace/config_schema.yml b/dace/config_schema.yml
index da35e61997..7afb06a50a 100644
--- a/dace/config_schema.yml
+++ b/dace/config_schema.yml
@@ -919,6 +919,13 @@ required:
                 description: >
                     Check for undefined symbols in memlets during SDFG validation.
 
+            check_race_conditions:
+                type: bool
+                default: false
+                title: Check race conditions
+                description: >
+                    Check for potential race conditions during validation.
+
     #############################################
     # Features for unit testing
 
diff --git a/dace/sdfg/validation.py b/dace/sdfg/validation.py
index e75099276f..f02a5003e9 100644
--- a/dace/sdfg/validation.py
+++ b/dace/sdfg/validation.py
@@ -1,17 +1,22 @@
-# Copyright 2019-2021 ETH Zurich and the DaCe authors. All rights reserved.
+# Copyright 2019-2024 ETH Zurich and the DaCe authors. All rights reserved.
 """ Exception classes and methods for validation of SDFGs. """
+
 import copy
-from dace.dtypes import DebugInfo
 import os
-from typing import TYPE_CHECKING, Dict, List, Set
 import warnings
+from collections import defaultdict
+from typing import TYPE_CHECKING, Dict, List, Set
+
+import networkx as nx
+
 from dace import dtypes, subsets, symbolic
+from dace.dtypes import DebugInfo
 
 if TYPE_CHECKING:
     import dace
+    from dace.memlet import Memlet
     from dace.sdfg import SDFG
     from dace.sdfg import graph as gr
-    from dace.memlet import Memlet
     from dace.sdfg.state import ControlFlowRegion
 
 ###########################################
@@ -34,8 +39,8 @@ def validate_control_flow_region(sdfg: 'SDFG',
                                  symbols: dict,
                                  references: Set[int] = None,
                                  **context: bool):
-    from dace.sdfg.state import SDFGState, ControlFlowRegion, ConditionalBlock
     from dace.sdfg.scope import is_in_scope
+    from dace.sdfg.state import ConditionalBlock, ControlFlowRegion, SDFGState
 
     if len(region.source_nodes()) > 1 and region.start_block is None:
         raise InvalidSDFGError("Starting block undefined", sdfg, None)
@@ -200,7 +205,7 @@ def validate_sdfg(sdfg: 'dace.sdfg.SDFG', references: Set[int] = None, **context
     # Avoid import loop
     from dace import data as dt
     from dace.codegen.targets import fpga
-    from dace.sdfg.scope import is_devicelevel_gpu, is_devicelevel_fpga
+    from dace.sdfg.scope import is_devicelevel_fpga, is_devicelevel_gpu
 
     references = references or set()
 
@@ -383,7 +388,8 @@ def validate_state(state: 'dace.sdfg.SDFGState',
     from dace.sdfg import SDFG
     from dace.sdfg import nodes as nd
     from dace.sdfg import utils as sdutil
-    from dace.sdfg.scope import scope_contains_scope, is_devicelevel_gpu, is_devicelevel_fpga
+    from dace.sdfg.scope import (is_devicelevel_fpga, is_devicelevel_gpu,
+                                 scope_contains_scope)
 
     sdfg = sdfg or state.parent
     state_id = state_id if state_id is not None else state.parent_graph.node_id(state)
@@ -839,6 +845,37 @@ def validate_state(state: 'dace.sdfg.SDFGState',
                     continue
                 raise error
 
+    if Config.get_bool('experimental.check_race_conditions'):
+        node_labels = []
+        write_accesses = defaultdict(list)
+        read_accesses = defaultdict(list)
+        for node in state.data_nodes():
+            node_labels.append(node.label)
+            write_accesses[node.label].extend(
+                [{'subset': e.data.dst_subset, 'node': node, 'wcr': e.data.wcr} for e in state.in_edges(node)])
+            read_accesses[node.label].extend(
+                [{'subset': e.data.src_subset, 'node': node} for e in state.out_edges(node)])
+
+        for node_label in node_labels:
+            writes = write_accesses[node_label]
+            reads = read_accesses[node_label]
+            # Check write-write data races.
+            for i in range(len(writes)):
+                for j in range(i+1, len(writes)):
+                    same_or_unreachable_nodes = (writes[i]['node'] == writes[j]['node'] or
+                                                 not nx.has_path(state.nx, writes[i]['node'], writes[j]['node']))
+                    no_wcr = writes[i]['wcr'] is None and writes[j]['wcr'] is None
+                    if same_or_unreachable_nodes and no_wcr:
+                        subsets_intersect = subsets.intersects(writes[i]['subset'], writes[j]['subset'])
+                        if subsets_intersect:
+                            warnings.warn(f'Memlet range overlap while writing to "{node}" in state "{state.label}"')
+            # Check read-write data races.
+            for write in writes:
+                for read in reads:
+                    if (not nx.has_path(state.nx, read['node'], write['node']) and
+                        subsets.intersects(write['subset'], read['subset'])):
+                        warnings.warn(f'Memlet range overlap while writing to "{node}" in state "{state.label}"')
+
     ########################################
 
 
diff --git a/tests/sdfg/warn_on_potential_data_race_test.py b/tests/sdfg/warn_on_potential_data_race_test.py
new file mode 100644
index 0000000000..8f17409a2f
--- /dev/null
+++ b/tests/sdfg/warn_on_potential_data_race_test.py
@@ -0,0 +1,316 @@
+# Copyright 2019-2024 ETH Zurich and the DaCe authors. All rights reserved.
+
+import warnings
+import dace
+import pytest
+
+def test_memlet_range_not_overlap_ranges():
+    sdfg = dace.SDFG('memlet_range_not_overlap_ranges')
+    state = sdfg.add_state()
+    N = dace.symbol("N", dtype=dace.int32)
+    sdfg.add_array("A", (N//2,), dace.int32)
+    A = state.add_access("A")
+    sdfg.add_array("B", (N,), dace.int32)
+    B = state.add_access("B")
+    state.add_mapped_tasklet(
+        name="first_tasklet",
+        code="b = a + 10",
+        inputs={"a": dace.Memlet(data="A", subset="k")},
+        outputs={"b": dace.Memlet(data="B", subset="k")},
+        map_ranges={"k": "0:N//2"},
+        external_edges=True,
+        input_nodes={"A": A},
+        output_nodes={"B": B}
+    )
+    state.add_mapped_tasklet(
+        name="second_tasklet",
+        code="b = a - 20",
+        inputs={"a": dace.Memlet(data="A", subset="k")},
+        outputs={"b": dace.Memlet(data="B", subset="k+N//2")},
+        map_ranges={"k": "0:N//2"},
+        external_edges=True,
+        input_nodes={"A": A},
+        output_nodes={"B": B}
+    )
+
+    with warnings.catch_warnings():
+        warnings.simplefilter("error", UserWarning)
+        with dace.config.set_temporary("experimental.check_race_conditions", value=True):
+            sdfg.validate()
+
+
+def test_memlet_range_write_write_overlap_ranges():
+    sdfg = dace.SDFG('memlet_range_overlap_ranges')
+    state = sdfg.add_state()
+    N = dace.symbol("N", dtype=dace.int32)
+    sdfg.add_array("A", (N,), dace.int32)
+    A = state.add_access("A")
+    sdfg.add_array("B", (N,), dace.int32)
+    B = state.add_access("B")
+    state.add_mapped_tasklet(
+        name="first_tasklet",
+        code="b = a + 10",
+        inputs={"a": dace.Memlet(data="A", subset="k")},
+        outputs={"b": dace.Memlet(data="B", subset="k")},
+        map_ranges={"k": "0:N"},
+        external_edges=True,
+        input_nodes={"A": A},
+        output_nodes={"B": B}
+    )
+    state.add_mapped_tasklet(
+        name="second_tasklet",
+        code="b = a - 20",
+        inputs={"a": dace.Memlet(data="A", subset="k")},
+        outputs={"b": dace.Memlet(data="B", subset="k")},
+        map_ranges={"k": "0:N"},
+        external_edges=True,
+        input_nodes={"A": A},
+        output_nodes={"B": B}
+    )
+
+    with pytest.warns(UserWarning):
+        with dace.config.set_temporary("experimental.check_race_conditions", value=True):
+            sdfg.validate()
+
+def test_memlet_range_write_read_overlap_ranges():
+    sdfg = dace.SDFG('memlet_range_write_read_overlap_ranges')
+    state = sdfg.add_state()
+    N = dace.symbol("N", dtype=dace.int32)
+    sdfg.add_array("A", (N,), dace.int32)
+    A_read = state.add_read("A")
+    A_write = state.add_write("A")
+    sdfg.add_array("B", (N,), dace.int32)
+    B = state.add_access("B")
+    sdfg.add_array("C", (N,), dace.int32)
+    C = state.add_access("C")
+    state.add_mapped_tasklet(
+        name="first_tasklet",
+        code="b = a + 10",
+        inputs={"a": dace.Memlet(data="A", subset="k")},
+        outputs={"b": dace.Memlet(data="B", subset="k")},
+        map_ranges={"k": "0:N"},
+        external_edges=True,
+        input_nodes={"A": A_read},
+        output_nodes={"B": B}
+    )
+    state.add_mapped_tasklet(
+        name="second_tasklet",
+        code="a = c - 20",
+        inputs={"c": dace.Memlet(data="C", subset="k")},
+        outputs={"a": dace.Memlet(data="A", subset="k")},
+        map_ranges={"k": "0:N"},
+        external_edges=True,
+        input_nodes={"C": C},
+        output_nodes={"A": A_write}
+    )
+
+    with pytest.warns(UserWarning):
+        with dace.config.set_temporary('experimental', 'check_race_conditions', value=True):
+            sdfg.validate()
+
+def test_memlet_overlap_ranges_two_access_nodes():
+    sdfg = dace.SDFG('memlet_range_write_read_overlap_ranges')
+    state = sdfg.add_state()
+    N = dace.symbol("N", dtype=dace.int32)
+    sdfg.add_array("A", (N,), dace.int32)
+    A1 = state.add_access("A")
+    A2 = state.add_access("A")
+    sdfg.add_array("B", (N,), dace.int32)
+    B1 = state.add_access("B")
+    B2 = state.add_access("B")
+
+    state.add_mapped_tasklet(
+        name="first_tasklet",
+        code="b = a + 10",
+        inputs={"a": dace.Memlet(data="A", subset="k")},
+        outputs={"b": dace.Memlet(data="B", subset="k")},
+        map_ranges={"k": "0:N"},
+        external_edges=True,
+        input_nodes={"A": A1},
+        output_nodes={"B": B1}
+    )
+    state.add_mapped_tasklet(
+        name="second_tasklet",
+        code="b = a - 20",
+        inputs={"a": dace.Memlet(data="A", subset="k")},
+        outputs={"b": dace.Memlet(data="B", subset="k")},
+        map_ranges={"k": "0:N"},
+        external_edges=True,
+        input_nodes={"A": A2},
+        output_nodes={"B": B2}
+    )
+
+    with pytest.warns(UserWarning):
+        with dace.config.set_temporary('experimental', 'check_race_conditions', value=True):
+            sdfg.validate()
+
+def test_memlet_overlap_symbolic_ranges():
+    sdfg = dace.SDFG('memlet_overlap_symbolic_ranges')
+    state = sdfg.add_state()
+    N = dace.symbol("N", dtype=dace.int32)
+    sdfg.add_array("A", (2*N,), dace.int32)
+    A = state.add_access("A")
+    sdfg.add_array("B", (2*N,), dace.int32)
+    B = state.add_access("B")
+
+    state.add_mapped_tasklet(
+        name="first_tasklet",
+        code="b = a + 10",
+        inputs={"a": dace.Memlet(data="A", subset="k")},
+        outputs={"b": dace.Memlet(data="B", subset="k")},
+        map_ranges={"k": "0:N"},
+        external_edges=True,
+        input_nodes={"A": A},
+        output_nodes={"B": B}
+    )
+    state.add_mapped_tasklet(
+        name="second_tasklet",
+        code="b = a - 20",
+        inputs={"a": dace.Memlet(data="A", subset="k")},
+        outputs={"b": dace.Memlet(data="B", subset="k")},
+        map_ranges={"k": "0:2*N"},
+        external_edges=True,
+        input_nodes={"A": A},
+        output_nodes={"B": B}
+    )
+
+    with pytest.warns(UserWarning):
+        with dace.config.set_temporary('experimental', 'check_race_conditions', value=True):
+            sdfg.validate()
+
+def test_constant_memlet_overlap():
+    sdfg = dace.SDFG('constant_memlet_overlap')
+    state = sdfg.add_state()
+    sdfg.add_array("A", (12,), dace.int32)
+    A = state.add_access("A")
+    sdfg.add_array("B", (12,), dace.int32)
+    B = state.add_access("B")
+
+    state.add_mapped_tasklet(
+        name="first_tasklet",
+        code="b = a + 10",
+        inputs={"a": dace.Memlet(data="A", subset="k")},
+        outputs={"b": dace.Memlet(data="B", subset="k")},
+        map_ranges={"k": "3:10"},
+        external_edges=True,
+        input_nodes={"A": A},
+        output_nodes={"B": B}
+    )
+    state.add_mapped_tasklet(
+        name="second_tasklet",
+        code="b = a - 20",
+        inputs={"a": dace.Memlet(data="A", subset="k")},
+        outputs={"b": dace.Memlet(data="B", subset="k")},
+        map_ranges={"k": "6:12"},
+        external_edges=True,
+        input_nodes={"A": A},
+        output_nodes={"B": B}
+    )
+
+    with pytest.warns(UserWarning):
+        with dace.config.set_temporary('experimental', 'check_race_conditions', value=True):
+            sdfg.validate()
+
+def test_constant_memlet_almost_overlap():
+    sdfg = dace.SDFG('constant_memlet_almost_overlap')
+    state = sdfg.add_state()
+    sdfg.add_array("A", (20,), dace.int32)
+    A = state.add_access("A")
+    sdfg.add_array("B", (20,), dace.int32)
+    B = state.add_access("B")
+
+    state.add_mapped_tasklet(
+        name="first_tasklet",
+        code="b = a + 10",
+        inputs={"a": dace.Memlet(data="A", subset="k")},
+        outputs={"b": dace.Memlet(data="B", subset="k")},
+        map_ranges={"k": "3:10"},
+        external_edges=True,
+        input_nodes={"A": A},
+        output_nodes={"B": B}
+    )
+    state.add_mapped_tasklet(
+        name="second_tasklet",
+        code="b = a - 20",
+        inputs={"a": dace.Memlet(data="A", subset="k")},
+        outputs={"b": dace.Memlet(data="B", subset="k")},
+        map_ranges={"k": "10:20"},
+        external_edges=True,
+        input_nodes={"A": A},
+        output_nodes={"B": B}
+    )
+
+    with warnings.catch_warnings():
+        warnings.simplefilter("error", UserWarning)
+        with dace.config.set_temporary('experimental', 'check_race_conditions', value=True):
+            sdfg.validate()
+
+def test_elementwise_map():
+    sdfg = dace.SDFG('elementwise_map')
+    state = sdfg.add_state()
+    sdfg.add_array("A", (20,), dace.int32)
+    A_read = state.add_read("A")
+    A_write = state.add_write("A")
+
+    state.add_mapped_tasklet(
+        name="first_tasklet",
+        code="aa = a + 10",
+        inputs={"a": dace.Memlet(data="A", subset="k")},
+        outputs={"aa": dace.Memlet(data="A", subset="k")},
+        map_ranges={"k": "0:20"},
+        external_edges=True,
+        input_nodes={"A": A_read},
+        output_nodes={"A": A_write}
+    )
+
+    with warnings.catch_warnings():
+        warnings.simplefilter("error", UserWarning)
+        with dace.config.set_temporary('experimental', 'check_race_conditions', value=True):
+            sdfg.validate()
+
+def test_memlet_overlap_with_wcr():
+    sdfg = dace.SDFG('memlet_overlap_with_wcr')
+    state = sdfg.add_state()
+    sdfg.add_array("A", (20,), dace.int32)
+    sdfg.add_array("B", (1,), dace.int32)
+    A = state.add_read("A")
+    B = state.add_write("B")
+
+    state.add_mapped_tasklet(
+        name="first_reduction",
+        code="b = a",
+        inputs={"a": dace.Memlet(data="A", subset="k")},
+        outputs={"b": dace.Memlet(data="B", subset="0", wcr="lambda old, new: old + new")},
+        map_ranges={"k": "0:20"},
+        external_edges=True,
+        input_nodes={"A": A},
+        output_nodes={"B": B}
+    )
+
+    state.add_mapped_tasklet(
+        name="second_reduction",
+        code="b = a",
+        inputs={"a": dace.Memlet(data="A", subset="k")},
+        outputs={"b": dace.Memlet(data="B", subset="0", wcr="lambda old, new: old + new")},
+        map_ranges={"k": "0:20"},
+        external_edges=True,
+        input_nodes={"A": A},
+        output_nodes={"B": B}
+    )
+
+    with warnings.catch_warnings():
+        warnings.simplefilter("error", UserWarning)
+        with dace.config.set_temporary('experimental', 'check_race_conditions', value=True):
+            sdfg.validate()
+
+
+if __name__ == '__main__':
+    test_memlet_range_not_overlap_ranges()
+    test_memlet_range_write_write_overlap_ranges()
+    test_memlet_range_write_read_overlap_ranges()
+    test_memlet_overlap_ranges_two_access_nodes()
+    test_memlet_overlap_symbolic_ranges()
+    test_constant_memlet_overlap()
+    test_constant_memlet_almost_overlap()
+    test_elementwise_map()
+    test_memlet_overlap_with_wcr()

From 7cb93f29820c8ad8caba5f75122d912192050f0f Mon Sep 17 00:00:00 2001
From: Tal Ben-Nun <tbennun@users.noreply.github.com>
Date: Tue, 29 Oct 2024 16:40:23 -0700
Subject: [PATCH 02/33] Python frontend stability and inline storage
 specification (#1711)

The PR adds a new syntax to support inline storage specification with
the `@` operator, supporting the following statements: `a = np.ones(M) @
dace.StorageType.CPU_ThreadLocal`.

This PR also fixes multiple minor issues in the Python frontend:
* `WarpTiling` did not respect sequential map schedules
* Non-sequence inputs for `numpy.fill` variants (e.g.,
`numpy.zeros(N)`)
* NumPy replacement syntax errors would sometimes not have source
information
* Fix type inference for nested scopes in Python frontend
* Dynamic thread block scheduling does not support multi-dimensional
maps
* Default schedule inference should use dynamic thread blocks if
they exist
* Type hints with storage type not being adhered to by the Python
frontend
* Validation issue #1562

The following changes were added as skipped tests and deferred to future PRs:
* Dynamic map range related issues: Fix deferred to #1696
* Dynamic thread block scheduling would not pass object to nested
functions: Fix deferred to future PR, see #1189 for more information
---
 dace/codegen/targets/cuda.py                  |  74 ++++++------
 dace/codegen/tools/type_inference.py          |   4 +-
 dace/dtypes.py                                |   2 -
 dace/frontend/python/newast.py                |  31 +++--
 dace/frontend/python/replacements.py          | 114 ++++++++----------
 dace/sdfg/infer_types.py                      |  10 +-
 dace/sdfg/sdfg.py                             |   8 +-
 dace/sdfg/validation.py                       |   3 +-
 dace/transformation/dataflow/warp_tiling.py   |   4 +
 dace/transformation/helpers.py                |  17 ++-
 tests/dynamic_tb_map_cudatest.py              |  70 ++++++++++-
 tests/numpy/array_creation_test.py            |  49 +++++++-
 tests/numpy/map_syntax_test.py                |  52 ++++++++
 .../device_annotations_test.py                |  49 ++++++--
 tests/sdfg/cycles_test.py                     |  19 ++-
 15 files changed, 370 insertions(+), 136 deletions(-)

diff --git a/dace/codegen/targets/cuda.py b/dace/codegen/targets/cuda.py
index f080f2cc62..1cf8919d74 100644
--- a/dace/codegen/targets/cuda.py
+++ b/dace/codegen/targets/cuda.py
@@ -23,8 +23,8 @@
 from dace.codegen.targets.target import IllegalCopy, TargetCodeGenerator, make_absolute
 from dace.config import Config
 from dace.frontend import operations
-from dace.sdfg import (SDFG, ScopeSubgraphView, SDFGState, has_dynamic_map_inputs,
-                       is_array_stream_view, is_devicelevel_gpu, nodes, scope_contains_scope)
+from dace.sdfg import (SDFG, ScopeSubgraphView, SDFGState, has_dynamic_map_inputs, is_array_stream_view,
+                       is_devicelevel_gpu, nodes, scope_contains_scope)
 from dace.sdfg import utils as sdutil
 from dace.sdfg.graph import MultiConnectorEdge
 from dace.sdfg.state import ControlFlowRegion, StateSubgraphView
@@ -68,6 +68,7 @@ def __init__(self, frame_codegen: 'DaCeCodeGenerator', sdfg: SDFG):
         dispatcher = self._dispatcher
 
         self.create_grid_barrier = False
+        self.dynamic_tbmap_type = None
         self.extra_nsdfg_args = []
         CUDACodeGen._in_device_code = False
         self._cpu_codegen: Optional['CPUCodeGen'] = None
@@ -892,8 +893,8 @@ def increment(streams):
 
         return max_streams, max_events
 
-    def _emit_copy(self, state_id: int, src_node: nodes.Node, src_storage: dtypes.StorageType,
-                   dst_node: nodes.Node, dst_storage: dtypes.StorageType, dst_schedule: dtypes.ScheduleType,
+    def _emit_copy(self, state_id: int, src_node: nodes.Node, src_storage: dtypes.StorageType, dst_node: nodes.Node,
+                   dst_storage: dtypes.StorageType, dst_schedule: dtypes.ScheduleType,
                    edge: Tuple[nodes.Node, str, nodes.Node, str, Memlet], sdfg: SDFG, cfg: ControlFlowRegion,
                    dfg: StateSubgraphView, callsite_stream: CodeIOStream) -> None:
         u, uconn, v, vconn, memlet = edge
@@ -1163,11 +1164,8 @@ def _emit_copy(self, state_id: int, src_node: nodes.Node, src_storage: dtypes.St
                             copysize=', '.join(_topy(copy_shape)),
                             is_async='true' if state_dfg.out_degree(dst_node) == 0 else 'false',
                             accum=accum or '::Copy',
-                            args=', '.join(
-                                [src_expr] + _topy(src_strides) + [dst_expr] + _topy(dst_strides) + custom_reduction
-                            )
-                        ),
-                        cfg, state_id, [src_node, dst_node])
+                            args=', '.join([src_expr] + _topy(src_strides) + [dst_expr] + _topy(dst_strides) +
+                                           custom_reduction)), cfg, state_id, [src_node, dst_node])
                 else:
                     callsite_stream.write(
                         ('    {func}<{type}, {bdims}, {copysize}, ' +
@@ -1236,8 +1234,12 @@ def _begin_streams(self, sdfg, state):
                         result.add(e.dst._cuda_stream)
         return result
 
-    def generate_state(self, sdfg: SDFG, cfg: ControlFlowRegion, state: SDFGState,
-                       function_stream: CodeIOStream, callsite_stream: CodeIOStream,
+    def generate_state(self,
+                       sdfg: SDFG,
+                       cfg: ControlFlowRegion,
+                       state: SDFGState,
+                       function_stream: CodeIOStream,
+                       callsite_stream: CodeIOStream,
                        generate_state_footer: bool = False) -> None:
         # Two modes: device-level state and if this state has active streams
         if CUDACodeGen._in_device_code:
@@ -1361,8 +1363,7 @@ def generate_devicelevel_state(self, sdfg: SDFG, cfg: ControlFlowRegion, state:
                                               "&& threadIdx.x == 0) "
                                               "{  // sub-graph begin", cfg, state.block_id)
                     elif write_scope == 'block':
-                        callsite_stream.write("if (threadIdx.x == 0) "
-                                              "{  // sub-graph begin", cfg, state.block_id)
+                        callsite_stream.write("if (threadIdx.x == 0) " "{  // sub-graph begin", cfg, state.block_id)
                     else:
                         callsite_stream.write("{  // subgraph begin", cfg, state.block_id)
                 else:
@@ -1985,16 +1986,13 @@ def generate_kernel_scope(self, sdfg: SDFG, cfg: ControlFlowRegion, dfg_scope: S
 
         # allocating shared memory for dynamic threadblock maps
         if has_dtbmap:
-            kernel_stream.write(
-                '__shared__ dace::'
-                'DynamicMap<{fine_grained}, {block_size}>'
-                '::shared_type dace_dyn_map_shared;'.format(
-                    fine_grained=('true'
-                                  if Config.get_bool('compiler', 'cuda', 'dynamic_map_fine_grained') else 'false'),
-                    block_size=functools.reduce(
-                        (lambda x, y: x * y),
-                        [int(x) for x in Config.get('compiler', 'cuda', 'dynamic_map_block_size').split(',')])), cfg,
-                state_id, node)
+            self.dynamic_tbmap_type = (
+                f'dace::DynamicMap<{"true" if Config.get_bool("compiler", "cuda", "dynamic_map_fine_grained") else "false"}, '
+                f'{functools.reduce((lambda x, y: x * y), [int(x) for x in Config.get("compiler", "cuda", "dynamic_map_block_size").split(",")])}>'
+                '::shared_type')
+            kernel_stream.write(f'__shared__ {self.dynamic_tbmap_type} dace_dyn_map_shared;', cfg, state_id, node)
+        else:
+            self.dynamic_tbmap_type = None
 
         # Add extra opening brace (dynamic map ranges, closed in MapExit
         # generator)
@@ -2072,8 +2070,8 @@ def generate_kernel_scope(self, sdfg: SDFG, cfg: ControlFlowRegion, dfg_scope: S
 
         # Generate conditions for this block's execution using min and max
         # element, e.g., skipping out-of-bounds threads in trailing block
-        # unless thsi is handled by another map down the line
-        if (not has_tbmap and not has_dtbmap and node.map.schedule != dtypes.ScheduleType.GPU_Persistent):
+        # unless this is handled by another map down the line
+        if ((not has_tbmap or has_dtbmap) and node.map.schedule != dtypes.ScheduleType.GPU_Persistent):
             dsym_end = [d + bs - 1 for d, bs in zip(dsym, self._block_dims)]
             minels = krange.min_element()
             maxels = krange.max_element()
@@ -2090,10 +2088,12 @@ def generate_kernel_scope(self, sdfg: SDFG, cfg: ControlFlowRegion, dfg_scope: S
                     condition += '%s < %s' % (v, _topy(maxel + 1))
                 if len(condition) > 0:
                     self._kernel_grid_conditions.append(f'if ({condition}) {{')
-                    kernel_stream.write('if (%s) {' % condition, cfg, state_id, scope_entry)
+                    if not has_dtbmap:
+                        kernel_stream.write('if (%s) {' % condition, cfg, state_id, scope_entry)
                 else:
                     self._kernel_grid_conditions.append('{')
-                    kernel_stream.write('{', cfg, state_id, scope_entry)
+                    if not has_dtbmap:
+                        kernel_stream.write('{', cfg, state_id, scope_entry)
 
         self._dispatcher.dispatch_subgraph(sdfg,
                                            cfg,
@@ -2112,6 +2112,7 @@ def generate_kernel_scope(self, sdfg: SDFG, cfg: ControlFlowRegion, dfg_scope: S
         self._kernel_state = None
         CUDACodeGen._in_device_code = False
         self._grid_dims = None
+        self.dynamic_tbmap_type = None
 
     def get_next_scope_entries(self, dfg, scope_entry):
         parent_scope_entry = dfg.entry_node(scope_entry)
@@ -2179,10 +2180,8 @@ def generate_devicelevel_scope(self, sdfg: SDFG, cfg: ControlFlowRegion, dfg_sco
                 current_sdfg = current_state.parent
             if not outer_scope:
                 raise ValueError(f'Failed to find the outer scope of {scope_entry}')
-            callsite_stream.write(
-                'if ({} < {}) {{'.format(outer_scope.map.params[0],
-                                         _topy(subsets.Range(outer_scope.map.range[::-1]).max_element()[0] + 1)), cfg,
-                state_id, scope_entry)
+            for cond in self._kernel_grid_conditions:
+                callsite_stream.write(cond, cfg, state_id, scope_entry)
 
             # NOTE: Dynamic map inputs must be defined both outside and inside the dynamic Map schedule.
             # They define inside the schedule the bounds of the any nested Maps.
@@ -2205,8 +2204,9 @@ def generate_devicelevel_scope(self, sdfg: SDFG, cfg: ControlFlowRegion, dfg_sco
                 '__dace_dynmap_begin = {begin};\n'
                 '__dace_dynmap_end = {end};'.format(begin=dynmap_begin, end=dynmap_end), cfg, state_id, scope_entry)
 
-            # close if
-            callsite_stream.write('}', cfg, state_id, scope_entry)
+            # Close kernel grid conditions
+            for _ in self._kernel_grid_conditions:
+                callsite_stream.write('}', cfg, state_id, scope_entry)
 
             callsite_stream.write(
                 'dace::DynamicMap<{fine_grained}, {bsize}>::'
@@ -2215,7 +2215,7 @@ def generate_devicelevel_scope(self, sdfg: SDFG, cfg: ControlFlowRegion, dfg_sco
                 'auto {param}) {{'.format(fine_grained=('true' if Config.get_bool(
                     'compiler', 'cuda', 'dynamic_map_fine_grained') else 'false'),
                                           bsize=total_block_size,
-                                          kmapIdx=outer_scope.map.params[0],
+                                          kmapIdx=outer_scope.map.params[-1],
                                           param=dynmap_var), cfg, state_id, scope_entry)
 
             for e in dace.sdfg.dynamic_map_inputs(dfg, scope_entry):
@@ -2556,8 +2556,8 @@ def generate_devicelevel_scope(self, sdfg: SDFG, cfg: ControlFlowRegion, dfg_sco
                 for cond in self._kernel_grid_conditions:
                     callsite_stream.write(cond, cfg, state_id, scope_entry)
 
-    def generate_node(self, sdfg: SDFG, cfg: ControlFlowRegion, dfg: StateSubgraphView, state_id: int,
-                      node: nodes.Node, function_stream: CodeIOStream, callsite_stream: CodeIOStream) -> None:
+    def generate_node(self, sdfg: SDFG, cfg: ControlFlowRegion, dfg: StateSubgraphView, state_id: int, node: nodes.Node,
+                      function_stream: CodeIOStream, callsite_stream: CodeIOStream) -> None:
         if self.node_dispatch_predicate(sdfg, dfg, node):
             # Dynamically obtain node generator according to class name
             gen = getattr(self, '_generate_' + type(node).__name__, False)
@@ -2594,6 +2594,8 @@ def generate_nsdfg_arguments(self, sdfg, cfg, dfg, state, node):
         result = self._cpu_codegen.generate_nsdfg_arguments(sdfg, cfg, dfg, state, node)
         if self.create_grid_barrier:
             result.append(('cub::GridBarrier&', '__gbar', '__gbar'))
+        if self.dynamic_tbmap_type:
+            result.append((f'{self.dynamic_tbmap_type}&', 'dace_dyn_map_shared', 'dace_dyn_map_shared'))
 
         # Add data from nested SDFGs to kernel arguments
         result.extend([(atype, aname, aname) for atype, aname, _ in self.extra_nsdfg_args])
diff --git a/dace/codegen/tools/type_inference.py b/dace/codegen/tools/type_inference.py
index 893866522f..8f8dd84151 100644
--- a/dace/codegen/tools/type_inference.py
+++ b/dace/codegen/tools/type_inference.py
@@ -9,7 +9,7 @@
 
 import numpy as np
 import ast
-from dace import dtypes
+from dace import data, dtypes
 from dace import symbolic
 from dace.codegen import cppunparse
 from dace.symbolic import symbol, SymExpr, symstr
@@ -286,6 +286,8 @@ def _Name(t, symbols, inferred_symbols):
                 inferred_type = dtypes.typeclass(inferred_type.type)
             elif isinstance(inferred_type, symbolic.symbol):
                 inferred_type = inferred_type.dtype
+            elif isinstance(inferred_type, data.Data):
+                inferred_type = inferred_type.dtype
         elif t_id in inferred_symbols:
             inferred_type = inferred_symbols[t_id]
         return inferred_type
diff --git a/dace/dtypes.py b/dace/dtypes.py
index c5f9bb4732..a016ac60e2 100644
--- a/dace/dtypes.py
+++ b/dace/dtypes.py
@@ -1,10 +1,8 @@
 # Copyright 2019-2023 ETH Zurich and the DaCe authors. All rights reserved.
 """ A module that contains various DaCe type definitions. """
-from __future__ import print_function
 import ctypes
 import aenum
 import inspect
-import itertools
 import numpy
 import re
 from collections import OrderedDict
diff --git a/dace/frontend/python/newast.py b/dace/frontend/python/newast.py
index cacf15d785..78890c9cdd 100644
--- a/dace/frontend/python/newast.py
+++ b/dace/frontend/python/newast.py
@@ -1489,19 +1489,19 @@ def _symbols_from_params(self, params: List[Tuple[str, Union[str, dtypes.typecla
             else:
                 values = str(val).split(':')
                 if len(values) == 1:
-                    result[name] = symbolic.symbol(name, infer_expr_type(values[0], {**self.globals, **dyn_inputs}))
+                    result[name] = symbolic.symbol(name, infer_expr_type(values[0], {**self.defined, **dyn_inputs}))
                 elif len(values) == 2:
                     result[name] = symbolic.symbol(
                         name,
                         dtypes.result_type_of(infer_expr_type(values[0], {
-                            **self.globals,
+                            **self.defined,
                             **dyn_inputs
                         }), infer_expr_type(values[1], {
-                            **self.globals,
+                            **self.defined,
                             **dyn_inputs
                         })))
                 elif len(values) == 3:
-                    result[name] = symbolic.symbol(name, infer_expr_type(values[0], {**self.globals, **dyn_inputs}))
+                    result[name] = symbolic.symbol(name, infer_expr_type(values[0], {**self.defined, **dyn_inputs}))
                 else:
                     raise DaceSyntaxError(
                         self, None, "Invalid number of arguments in a range iterator. "
@@ -3258,18 +3258,23 @@ def visit_AnnAssign(self, node: ast.AnnAssign):
             dtype = astutils.evalnode(node.annotation, {**self.globals, **self.defined})
             if isinstance(dtype, data.Data):
                 simple_type = dtype.dtype
+                storage = dtype.storage
             else:
                 simple_type = dtype
+                storage = dtypes.StorageType.Default
             if not isinstance(simple_type, dtypes.typeclass):
                 raise TypeError
         except:
             dtype = None
+            storage = dtypes.StorageType.Default
             type_name = rname(node.annotation)
             warnings.warn('typeclass {} is not supported'.format(type_name))
         if node.value is None and dtype is not None:  # Annotating type without assignment
             self.annotated_types[rname(node.target)] = dtype
             return
-        self._visit_assign(node, node.target, None, dtype=dtype)
+        results = self._visit_assign(node, node.target, None, dtype=dtype)
+        if storage != dtypes.StorageType.Default:
+            self.sdfg.arrays[results[0][0]].storage = storage
 
     def _visit_assign(self, node, node_target, op, dtype=None, is_return=False):
         # Get targets (elts) and results
@@ -3563,6 +3568,8 @@ def _visit_assign(self, node, node_target, op, dtype=None, is_return=False):
                 self.cfg_target.add_edge(self.last_block, output_indirection, dace.sdfg.InterstateEdge())
                 self.last_block = output_indirection
 
+        return results
+
     def visit_AugAssign(self, node: ast.AugAssign):
         self._visit_assign(node, node.target, augassign_ops[type(node.op).__name__])
 
@@ -4623,10 +4630,16 @@ def visit_Call(self, node: ast.Call, create_callbacks=False):
         self._add_state('call_%d' % node.lineno)
         self.last_block.set_default_lineinfo(self.current_lineinfo)
 
-        if found_ufunc:
-            result = func(self, node, self.sdfg, self.last_block, ufunc_name, args, keywords)
-        else:
-            result = func(self, self.sdfg, self.last_block, *args, **keywords)
+        try:
+            if found_ufunc:
+                result = func(self, node, self.sdfg, self.last_block, ufunc_name, args, keywords)
+            else:
+                result = func(self, self.sdfg, self.last_block, *args, **keywords)
+        except DaceSyntaxError as ex:
+            # Attach source information to exception
+            if ex.node is None:
+                ex.node = node
+            raise
 
         self.last_block.set_default_lineinfo(None)
 
diff --git a/dace/frontend/python/replacements.py b/dace/frontend/python/replacements.py
index 5e6118a34b..537fef97bf 100644
--- a/dace/frontend/python/replacements.py
+++ b/dace/frontend/python/replacements.py
@@ -322,24 +322,30 @@ def _numpy_full(pv: ProgramVisitor,
         is_data = True
         vtype = sdfg.arrays[fill_value].dtype
     dtype = dtype or vtype
+
+    # Handle one-dimensional inputs
+    if isinstance(shape, (Number, str)) or symbolic.issymbolic(shape):
+        shape = [shape]
+
+    if any(isinstance(s, str) for s in shape):
+        raise DaceSyntaxError(
+            pv, None, f'Data-dependent shape {shape} is currently not allowed. Only constants '
+            'and symbolic values can be used.')
+
     name, _ = sdfg.add_temp_transient(shape, dtype)
 
     if is_data:
         state.add_mapped_tasklet(
-            '_numpy_full_', {
-                "__i{}".format(i): "0: {}".format(s)
-                for i, s in enumerate(shape)
-            },
+            '_numpy_full_', {"__i{}".format(i): "0: {}".format(s)
+                             for i, s in enumerate(shape)},
             dict(__inp=dace.Memlet(data=fill_value, subset='0')),
             "__out = __inp",
             dict(__out=dace.Memlet.simple(name, ",".join(["__i{}".format(i) for i in range(len(shape))]))),
             external_edges=True)
     else:
         state.add_mapped_tasklet(
-            '_numpy_full_', {
-                "__i{}".format(i): "0: {}".format(s)
-                for i, s in enumerate(shape)
-            }, {},
+            '_numpy_full_', {"__i{}".format(i): "0: {}".format(s)
+                             for i, s in enumerate(shape)}, {},
             "__out = {}".format(fill_value),
             dict(__out=dace.Memlet.simple(name, ",".join(["__i{}".format(i) for i in range(len(shape))]))),
             external_edges=True)
@@ -459,10 +465,8 @@ def _numpy_flip(pv: ProgramVisitor, sdfg: SDFG, state: SDFGState, arr: str, axis
     inpidx = ','.join([f'__i{i}' for i in range(ndim)])
     outidx = ','.join([f'{s} - __i{i} - 1' if a else f'__i{i}' for i, (a, s) in enumerate(zip(axis, desc.shape))])
     state.add_mapped_tasklet(name="_numpy_flip_",
-                             map_ranges={
-                                 f'__i{i}': f'0:{s}:1'
-                                 for i, s in enumerate(desc.shape)
-                             },
+                             map_ranges={f'__i{i}': f'0:{s}:1'
+                                         for i, s in enumerate(desc.shape)},
                              inputs={'__inp': Memlet(f'{arr}[{inpidx}]')},
                              code='__out = __inp',
                              outputs={'__out': Memlet(f'{arr_copy}[{outidx}]')},
@@ -532,10 +536,8 @@ def _numpy_rot90(pv: ProgramVisitor, sdfg: SDFG, state: SDFGState, arr: str, k=1
 
     outidx = ','.join(out_indices)
     state.add_mapped_tasklet(name="_rot90_",
-                             map_ranges={
-                                 f'__i{i}': f'0:{s}:1'
-                                 for i, s in enumerate(desc.shape)
-                             },
+                             map_ranges={f'__i{i}': f'0:{s}:1'
+                                         for i, s in enumerate(desc.shape)},
                              inputs={'__inp': Memlet(f'{arr}[{inpidx}]')},
                              code='__out = __inp',
                              outputs={'__out': Memlet(f'{arr_copy}[{outidx}]')},
@@ -644,7 +646,8 @@ def _elementwise(pv: 'ProgramVisitor',
     else:
         state.add_mapped_tasklet(
             name="_elementwise_",
-            map_ranges={f'__i{dim}': f'0:{N}' for dim, N in enumerate(inparr.shape)},
+            map_ranges={f'__i{dim}': f'0:{N}'
+                        for dim, N in enumerate(inparr.shape)},
             inputs={'__inp': Memlet.simple(in_array, ','.join([f'__i{dim}' for dim in range(len(inparr.shape))]))},
             code=code,
             outputs={'__out': Memlet.simple(out_array, ','.join([f'__i{dim}' for dim in range(len(inparr.shape))]))},
@@ -694,10 +697,8 @@ def _simple_call(sdfg: SDFG, state: SDFGState, inpname: str, func: str, restype:
     else:
         state.add_mapped_tasklet(
             name=func,
-            map_ranges={
-                '__i%d' % i: '0:%s' % n
-                for i, n in enumerate(inparr.shape)
-            },
+            map_ranges={'__i%d' % i: '0:%s' % n
+                        for i, n in enumerate(inparr.shape)},
             inputs={'__inp': Memlet.simple(inpname, ','.join(['__i%d' % i for i in range(len(inparr.shape))]))},
             code='__out = {f}(__inp)'.format(f=func),
             outputs={'__out': Memlet.simple(outname, ','.join(['__i%d' % i for i in range(len(inparr.shape))]))},
@@ -1046,27 +1047,22 @@ def _argminmax(pv: ProgramVisitor,
     code = "__init = _val_and_idx(val={}, idx=-1)".format(
         dtypes.min_value(a_arr.dtype) if func == 'max' else dtypes.max_value(a_arr.dtype))
 
-    nest.add_state().add_mapped_tasklet(name="_arg{}_convert_".format(func),
-                                        map_ranges={
-                                            '__i%d' % i: '0:%s' % n
-                                            for i, n in enumerate(a_arr.shape) if i != axis
-                                        },
-                                        inputs={},
-                                        code=code,
-                                        outputs={
-                                            '__init':
-                                            Memlet.simple(
-                                                reduced_structs,
-                                                ','.join('__i%d' % i for i in range(len(a_arr.shape)) if i != axis))
-                                        },
-                                        external_edges=True)
+    nest.add_state().add_mapped_tasklet(
+        name="_arg{}_convert_".format(func),
+        map_ranges={'__i%d' % i: '0:%s' % n
+                    for i, n in enumerate(a_arr.shape) if i != axis},
+        inputs={},
+        code=code,
+        outputs={
+            '__init': Memlet.simple(reduced_structs,
+                                    ','.join('__i%d' % i for i in range(len(a_arr.shape)) if i != axis))
+        },
+        external_edges=True)
 
     nest.add_state().add_mapped_tasklet(
         name="_arg{}_reduce_".format(func),
-        map_ranges={
-            '__i%d' % i: '0:%s' % n
-            for i, n in enumerate(a_arr.shape)
-        },
+        map_ranges={'__i%d' % i: '0:%s' % n
+                    for i, n in enumerate(a_arr.shape)},
         inputs={'__in': Memlet.simple(a, ','.join('__i%d' % i for i in range(len(a_arr.shape))))},
         code="__out = _val_and_idx(idx={}, val=__in)".format("__i%d" % axis),
         outputs={
@@ -1086,10 +1082,8 @@ def _argminmax(pv: ProgramVisitor,
 
         nest.add_state().add_mapped_tasklet(
             name="_arg{}_extract_".format(func),
-            map_ranges={
-                '__i%d' % i: '0:%s' % n
-                for i, n in enumerate(a_arr.shape) if i != axis
-            },
+            map_ranges={'__i%d' % i: '0:%s' % n
+                        for i, n in enumerate(a_arr.shape) if i != axis},
             inputs={
                 '__in': Memlet.simple(reduced_structs,
                                       ','.join('__i%d' % i for i in range(len(a_arr.shape)) if i != axis))
@@ -1212,10 +1206,9 @@ def _unop(sdfg: SDFG, state: SDFGState, op1: str, opcode: str, opname: str):
         opcode = 'not'
 
     name, _ = sdfg.add_temp_transient(arr1.shape, restype, arr1.storage)
-    state.add_mapped_tasklet("_%s_" % opname, {
-        '__i%d' % i: '0:%s' % s
-        for i, s in enumerate(arr1.shape)
-    }, {'__in1': Memlet.simple(op1, ','.join(['__i%d' % i for i in range(len(arr1.shape))]))},
+    state.add_mapped_tasklet("_%s_" % opname, {'__i%d' % i: '0:%s' % s
+                                               for i, s in enumerate(arr1.shape)},
+                             {'__in1': Memlet.simple(op1, ','.join(['__i%d' % i for i in range(len(arr1.shape))]))},
                              '__out = %s __in1' % opcode,
                              {'__out': Memlet.simple(name, ','.join(['__i%d' % i for i in range(len(arr1.shape))]))},
                              external_edges=True)
@@ -4316,10 +4309,8 @@ def _ndarray_fill(pv: ProgramVisitor, sdfg: SDFG, state: SDFGState, arr: str, va
     shape = sdfg.arrays[arr].shape
     state.add_mapped_tasklet(
         '_numpy_fill_',
-        map_ranges={
-            f"__i{dim}": f"0:{s}"
-            for dim, s in enumerate(shape)
-        },
+        map_ranges={f"__i{dim}": f"0:{s}"
+                    for dim, s in enumerate(shape)},
         inputs=inputs,
         code=f"__out = {body}",
         outputs={'__out': dace.Memlet.simple(arr, ",".join([f"__i{dim}" for dim in range(len(shape))]))},
@@ -4544,6 +4535,13 @@ def _ndarray_astype(pv: ProgramVisitor, sdfg: SDFG, state: SDFGState, arr: str,
     return _datatype_converter(sdfg, state, arr, dtype)[0]
 
 
+@oprepo.replaces_operator('Array', 'MatMult', otherclass='StorageType')
+def _cast_storage(visitor: 'ProgramVisitor', sdfg: SDFG, state: SDFGState, arr: str, stype: dace.StorageType) -> str:
+    desc = sdfg.arrays[arr]
+    desc.storage = stype
+    return arr
+
+
 # Replacements that need ufuncs ###############################################
 # TODO: Fix by separating to different modules and importing
 
@@ -4747,13 +4745,7 @@ def _tensordot(pv: 'ProgramVisitor',
 
 @oprepo.replaces("cupy._core.core.ndarray")
 @oprepo.replaces("cupy.ndarray")
-def _define_cupy_local(
-    pv: "ProgramVisitor",
-    sdfg: SDFG,
-    state: SDFGState,
-    shape: Shape,
-    dtype: typeclass
-):
+def _define_cupy_local(pv: "ProgramVisitor", sdfg: SDFG, state: SDFGState, shape: Shape, dtype: typeclass):
     """Defines a local array in a DaCe program."""
     if not isinstance(shape, (list, tuple)):
         shape = [shape]
@@ -4781,10 +4773,8 @@ def _cupy_full(pv: ProgramVisitor,
     name, _ = sdfg.add_temp_transient(shape, dtype, storage=dtypes.StorageType.GPU_Global)
 
     state.add_mapped_tasklet(
-        '_cupy_full_', {
-            "__i{}".format(i): "0: {}".format(s)
-            for i, s in enumerate(shape)
-        }, {},
+        '_cupy_full_', {"__i{}".format(i): "0: {}".format(s)
+                        for i, s in enumerate(shape)}, {},
         "__out = {}".format(fill_value),
         dict(__out=dace.Memlet.simple(name, ",".join(["__i{}".format(i) for i in range(len(shape))]))),
         external_edges=True)
diff --git a/dace/sdfg/infer_types.py b/dace/sdfg/infer_types.py
index cf58cf76cc..97010e95a7 100644
--- a/dace/sdfg/infer_types.py
+++ b/dace/sdfg/infer_types.py
@@ -116,8 +116,7 @@ def infer_connector_types(sdfg: SDFG):
             for e in state.out_edges(node):
                 cname = e.src_conn
                 if cname and node.out_connectors[cname] is None:
-                    raise TypeError('Ambiguous or uninferable type in'
-                                    ' connector "%s" of node "%s"' % (cname, node))
+                    raise TypeError('Ambiguous or uninferable type in' ' connector "%s" of node "%s"' % (cname, node))
 
 
 #############################################################################
@@ -301,6 +300,12 @@ def _set_default_schedule_in_scope(state: SDFGState,
     else:
         child_schedule = _determine_child_schedule(parent_schedules)
 
+        # Special case for dynamic thread-block neighboring schedules
+        if child_schedule == dtypes.ScheduleType.GPU_ThreadBlock:
+            from dace.transformation.helpers import gpu_map_has_explicit_dyn_threadblocks  # Avoid import loops
+            if gpu_map_has_explicit_dyn_threadblocks(state, parent_node):
+                child_schedule = dtypes.ScheduleType.GPU_ThreadBlock_Dynamic
+
     # Set child schedule type in scope
     for node in child_nodes[parent_node]:
         # Set default schedule types
@@ -393,6 +398,7 @@ def _get_storage_from_parent(data_name: str, sdfg: SDFG) -> dtypes.StorageType:
 
     raise ValueError(f'Could not find data descriptor {data_name} in parent SDFG')
 
+
 def infer_aliasing(node: nodes.NestedSDFG, sdfg: SDFG, state: SDFGState) -> None:
     """
     Infers aliasing information on nested SDFG arrays based on external edges and connectors.
diff --git a/dace/sdfg/sdfg.py b/dace/sdfg/sdfg.py
index 38a41236a6..f25a6e24d5 100644
--- a/dace/sdfg/sdfg.py
+++ b/dace/sdfg/sdfg.py
@@ -761,13 +761,13 @@ def add_symbol(self, name, stype, find_new_name: bool = False):
             if name in self.symbols:
                 raise FileExistsError(f'Symbol "{name}" already exists in SDFG')
             if name in self.arrays:
-                raise FileExistsError(f'Can not create symbol "{name}", the name is used by a data descriptor.')
+                raise FileExistsError(f'Cannot create symbol "{name}", the name is used by a data descriptor.')
             if name in self._subarrays:
-                raise FileExistsError(f'Can not create symbol "{name}", the name is used by a subarray.')
+                raise FileExistsError(f'Cannot create symbol "{name}", the name is used by a subarray.')
             if name in self._rdistrarrays:
-                raise FileExistsError(f'Can not create symbol "{name}", the name is used by a RedistrArray.')
+                raise FileExistsError(f'Cannot create symbol "{name}", the name is used by a RedistrArray.')
             if name in self._pgrids:
-                raise FileExistsError(f'Can not create symbol "{name}", the name is used by a ProcessGrid.')
+                raise FileExistsError(f'Cannot create symbol "{name}", the name is used by a ProcessGrid.')
         if not isinstance(stype, dtypes.typeclass):
             stype = dtypes.dtype_to_typeclass(stype)
         self.symbols[name] = stype
diff --git a/dace/sdfg/validation.py b/dace/sdfg/validation.py
index f02a5003e9..2df9e17445 100644
--- a/dace/sdfg/validation.py
+++ b/dace/sdfg/validation.py
@@ -396,7 +396,6 @@ def validate_state(state: 'dace.sdfg.SDFGState',
     symbols = symbols or {}
     initialized_transients = (initialized_transients if initialized_transients is not None else {'__pystate'})
     references = references or set()
-    scope = state.scope_dict()
 
     # Obtain whether we are already in an accelerator context
     if not hasattr(context, 'in_gpu'):
@@ -426,6 +425,8 @@ def validate_state(state: 'dace.sdfg.SDFGState',
     if state.has_cycles():
         raise InvalidSDFGError('State should be acyclic but contains cycles', sdfg, state_id)
 
+    scope = state.scope_dict()
+
     for nid, node in enumerate(state.nodes()):
         # Reference check
         if id(node) in references:
diff --git a/dace/transformation/dataflow/warp_tiling.py b/dace/transformation/dataflow/warp_tiling.py
index 362b51d9ac..f9091950e3 100644
--- a/dace/transformation/dataflow/warp_tiling.py
+++ b/dace/transformation/dataflow/warp_tiling.py
@@ -55,6 +55,10 @@ def apply(self, graph: SDFGState, sdfg: SDFG) -> nodes.MapEntry:
         # Stride and offset all internal maps
         maps_to_stride = xfh.get_internal_scopes(graph, new_me, immediate=True)
         for nstate, nmap in maps_to_stride:
+            # Skip sequential maps
+            if nmap.schedule == dtypes.ScheduleType.Sequential:
+                continue
+
             nsdfg = nstate.parent
             nsdfg_node = nsdfg.parent_nsdfg_node
 
diff --git a/dace/transformation/helpers.py b/dace/transformation/helpers.py
index 6ca4602079..b7bf49e62b 100644
--- a/dace/transformation/helpers.py
+++ b/dace/transformation/helpers.py
@@ -934,11 +934,7 @@ def replicate_scope(sdfg: SDFG, state: SDFGState, scope: ScopeSubgraphView) -> S
     return ScopeSubgraphView(state, new_nodes, new_entry)
 
 
-def offset_map(state: SDFGState,
-               entry: nodes.MapEntry,
-               dim: int,
-               offset: symbolic.SymbolicType,
-               negative: bool = True):
+def offset_map(state: SDFGState, entry: nodes.MapEntry, dim: int, offset: symbolic.SymbolicType, negative: bool = True):
     """
     Offsets a map parameter and its contents by a value.
 
@@ -1270,6 +1266,17 @@ def gpu_map_has_explicit_threadblocks(state: SDFGState, entry: nodes.EntryNode)
     return False
 
 
+def gpu_map_has_explicit_dyn_threadblocks(state: SDFGState, entry: nodes.EntryNode) -> bool:
+    """
+    Returns True if GPU_Device map has explicit thread-block maps nested within.
+    """
+    internal_maps = get_internal_scopes(state, entry)
+    if any(m.schedule == dtypes.ScheduleType.GPU_ThreadBlock_Dynamic for _, m in internal_maps):
+        return True
+
+    return False
+
+
 def reconnect_edge_through_map(
         state: SDFGState, edge: graph.MultiConnectorEdge[Memlet], new_node: Union[nodes.EntryNode, nodes.ExitNode],
         keep_src: bool) -> Tuple[graph.MultiConnectorEdge[Memlet], graph.MultiConnectorEdge[Memlet]]:
diff --git a/tests/dynamic_tb_map_cudatest.py b/tests/dynamic_tb_map_cudatest.py
index b24e5f2ea6..edc1eac9f2 100644
--- a/tests/dynamic_tb_map_cudatest.py
+++ b/tests/dynamic_tb_map_cudatest.py
@@ -12,10 +12,8 @@
 
 @dace.program(dace.uint32[H + 1], dace.uint32[nnz], dace.float32[nnz], dace.float32[W], dace.float32[H])
 def spmv(A_row, A_col, A_val, x, b):
-
     @dace.mapscope(_[0:H])
     def compute_row(i):
-
         @dace.map(_[A_row[i]:A_row[i + 1]])
         def compute(j):
             a << A_val[j]
@@ -292,8 +290,76 @@ def sddvm(D_vals: dace.float32[nnz_D], A2_crd: dace.int32[nnz_A], A2_pos: dace.i
     assert np.allclose(val, ref.data)
 
 
+@pytest.mark.gpu
+def test_dynamic_multidim_map():
+    @dace.program
+    def tester(a: dace.float32[H, W, nnz]):
+        A = dace.ndarray([H, W, nnz], dtype=dace.float32, storage=dace.StorageType.GPU_Global)
+        A[:] = a
+        for i, j in dace.map[0:H, 0:W] @ dace.ScheduleType.GPU_Device:
+            for k in dace.map[0:nnz] @ dace.ScheduleType.GPU_ThreadBlock_Dynamic:
+                A[i, j, k] = i * 110 + j * 11 + k
+        a[:] = A
+
+    a = np.zeros((10, 11, 65), dtype=np.float32)
+    tester(a)
+    assert np.allclose(a, np.fromfunction(lambda i, j, k: i * 110 + j * 11 + k, (10, 11, 65), dtype=np.float32))
+
+
+@pytest.mark.skip('Nested maps with work-stealing thread-block schedule are currently unsupported')
+def test_dynamic_nested_map():
+    @dace.program
+    def nested2(A: dace.float32[W], i: dace.int32, j: dace.int32):
+        A[j] = i * 10 + j
+
+    @dace.program
+    def nested1(A: dace.float32[W], i: dace.int32):
+        for j in dace.map[0:W] @ dace.ScheduleType.GPU_ThreadBlock_Dynamic:
+            nested2(A, i, j)
+
+    @dace.program
+    def dynamic_nested_map(a: dace.float32[H, W]):
+        A = dace.ndarray([H, W], dtype=dace.float32, storage=dace.StorageType.GPU_Global)
+        A[:] = a
+        for i in dace.map[0:H] @ dace.ScheduleType.GPU_Device:
+            nested1(A[i], i)
+
+        a[:] = A
+
+    a = np.zeros((10, 11), dtype=np.float32)
+    sdfg = dynamic_nested_map.to_sdfg(simplify=False)
+    for _, _, arr in sdfg.arrays_recursive():
+        if arr.storage in (dace.StorageType.GPU_Shared, dace.StorageType.Default):
+            arr.storage = dace.StorageType.Register
+    sdfg(a, H=10, W=11)
+    assert np.allclose(a, np.fromfunction(lambda i, j: i * 10 + j, (10, 11), dtype=np.float32))
+
+
+@pytest.mark.gpu
+def test_dynamic_default_schedule():
+    N = dace.symbol('N')
+
+    @dace.program
+    def tester(a: dace.float32[N, 10]):
+        A = dace.ndarray([N, 10], dtype=dace.float32, storage=dace.StorageType.GPU_Global)
+        A[:] = a
+        for i in dace.map[0:N] @ dace.ScheduleType.GPU_Device:
+            smem = np.empty((10, ), dtype=np.float32) @ dace.StorageType.GPU_Shared
+            smem[:] = 1
+            for j in dace.map[0:10] @ dace.ScheduleType.GPU_ThreadBlock_Dynamic:
+                A[i, j] = i * 65 + smem[j]
+        a[:] = A
+
+    a = np.zeros((65, 10), dtype=np.float32)
+    tester(a)
+    assert np.allclose(a, np.fromfunction(lambda i, j: i * 65 + 1, (65, 10), dtype=np.float32))
+
+
 if __name__ == '__main__':
     test_dynamic_map()
     test_dynamic_maps()
     test_nested_dynamic_map()
     test_dynamic_map_with_step()
+    test_dynamic_multidim_map()
+    # test_dynamic_nested_map()
+    test_dynamic_default_schedule()
diff --git a/tests/numpy/array_creation_test.py b/tests/numpy/array_creation_test.py
index 85908c7a1f..7329b48b3f 100644
--- a/tests/numpy/array_creation_test.py
+++ b/tests/numpy/array_creation_test.py
@@ -1,7 +1,9 @@
 # Copyright 2019-2021 ETH Zurich and the DaCe authors. All rights reserved.
 import dace
+from dace.frontend.python.common import DaceSyntaxError
 import numpy as np
 from common import compare_numpy_output
+import pytest
 
 # M = dace.symbol('M')
 # N = dace.symbol('N')
@@ -154,7 +156,7 @@ def test_arange_6():
 def program_strides_0():
     A = dace.ndarray((2, 2), dtype=dace.int32, strides=(2, 1))
     for i, j in dace.map[0:2, 0:2]:
-            A[i, j] = i * 2 + j
+        A[i, j] = i * 2 + j
     return A
 
 
@@ -168,7 +170,7 @@ def test_strides_0():
 def program_strides_1():
     A = dace.ndarray((2, 2), dtype=dace.int32, strides=(4, 2))
     for i, j in dace.map[0:2, 0:2]:
-            A[i, j] = i * 2 + j
+        A[i, j] = i * 2 + j
     return A
 
 
@@ -182,7 +184,7 @@ def test_strides_1():
 def program_strides_2():
     A = dace.ndarray((2, 2), dtype=dace.int32, strides=(1, 2))
     for i, j in dace.map[0:2, 0:2]:
-            A[i, j] = i * 2 + j
+        A[i, j] = i * 2 + j
     return A
 
 
@@ -196,7 +198,7 @@ def test_strides_2():
 def program_strides_3():
     A = dace.ndarray((2, 2), dtype=dace.int32, strides=(2, 4))
     for i, j in dace.map[0:2, 0:2]:
-            A[i, j] = i * 2 + j
+        A[i, j] = i * 2 + j
     return A
 
 
@@ -206,6 +208,42 @@ def test_strides_3():
     assert np.allclose(A, [[0, 1], [2, 3]])
 
 
+def test_zeros_symbolic_size_scalar():
+    K = dace.symbol('K')
+
+    @dace.program
+    def zeros_symbolic_size():
+        return np.zeros((K), dtype=np.uint32)
+
+    out = zeros_symbolic_size(K=10)
+    assert (list(out.shape) == [10])
+    assert (out.dtype == np.uint32)
+
+
+def test_ones_scalar_size_scalar():
+
+    @dace.program
+    def ones_scalar_size(k: dace.int32):
+        a = np.ones(k, dtype=np.uint32)
+        return np.sum(a)
+
+    with pytest.raises(DaceSyntaxError):
+        out = ones_scalar_size(20)
+        assert out == 20
+
+
+def test_ones_scalar_size():
+
+    @dace.program
+    def ones_scalar_size(k: dace.int32):
+        a = np.ones((k, k), dtype=np.uint32)
+        return np.sum(a)
+
+    with pytest.raises(DaceSyntaxError):
+        out = ones_scalar_size(20)
+        assert out == 20 * 20
+
+
 if __name__ == "__main__":
     test_empty()
     test_empty_like1()
@@ -233,3 +271,6 @@ def test_strides_3():
     test_strides_1()
     test_strides_2()
     test_strides_3()
+    test_zeros_symbolic_size_scalar()
+    test_ones_scalar_size_scalar()
+    test_ones_scalar_size()
diff --git a/tests/numpy/map_syntax_test.py b/tests/numpy/map_syntax_test.py
index fe7af1d644..27a0cfe018 100644
--- a/tests/numpy/map_syntax_test.py
+++ b/tests/numpy/map_syntax_test.py
@@ -1,6 +1,7 @@
 # Copyright 2019-2021 ETH Zurich and the DaCe authors. All rights reserved.
 import numpy as np
 import dace
+import pytest
 
 M, N, K = (dace.symbol(name) for name in ['M', 'N', 'K'])
 
@@ -35,6 +36,57 @@ def test_map_python():
     assert np.allclose(A[:, 1:], B[:, 1:])
 
 
+@pytest.mark.skip('Fails due to bug in Python frontend')
+def test_nested_map_with_indirection():
+    N = dace.symbol('N')
+
+    @dace.program
+    def indirect_to_indirect(arr1: dace.float64[N], ind: dace.int32[10], arr2: dace.float64[N]):
+        for i in dace.map[0:9]:
+            begin, end, stride = ind[i], ind[i + 1], 1
+            for _ in dace.map[0:1]:
+                for j in dace.map[begin:end:stride]:
+                    arr2[j] = arr1[j] + i
+
+    a = np.random.rand(50)
+    b = np.zeros(50)
+    ind = np.array([0, 5, 10, 15, 20, 25, 30, 35, 40, 45], dtype=np.int32)
+    sdfg = indirect_to_indirect.to_sdfg(simplify=False)
+    sdfg(a, ind, b)
+
+    ref = np.zeros(50)
+    for i in range(9):
+        begin, end = ind[i], ind[i + 1]
+        ref[begin:end] = a[begin:end] + i
+
+    assert np.allclose(b, ref)
+
+
+@pytest.mark.skip('Fails due to bug in Python frontend')
+def test_dynamic_map_range_scalar():
+    """
+    From issue #650.
+    """
+
+    @dace.program
+    def test(A: dace.float64[20], B: dace.float64[20]):
+        N = dace.define_local_scalar(dace.int32)
+        N = 5
+        for i in dace.map[0:N]:
+            for j in dace.map[0:N]:
+                with dace.tasklet:
+                    a << A[i]
+                    b >> B[j]
+                    b = a + 1
+
+    A = np.random.rand(20)
+    B = np.zeros(20)
+    test(A, B)
+    assert np.allclose(B[:5], A[:5] + 1)
+
+
 if __name__ == '__main__':
     test_copy3d()
     test_map_python()
+    # test_nested_map_with_indirection()
+    # test_dynamic_map_range_scalar()
diff --git a/tests/python_frontend/device_annotations_test.py b/tests/python_frontend/device_annotations_test.py
index 65c8501b23..d6b512f00b 100644
--- a/tests/python_frontend/device_annotations_test.py
+++ b/tests/python_frontend/device_annotations_test.py
@@ -1,16 +1,19 @@
-# Copyright 2019-2022 ETH Zurich and the DaCe authors. All rights reserved.
+# Copyright 2019-2024 ETH Zurich and the DaCe authors. All rights reserved.
 import dace
 import pytest
+import numpy as np
 
 from dace.dtypes import StorageType, DeviceType, ScheduleType
 from dace import dtypes
 
-cupy = pytest.importorskip("cupy")
+try:
+    import cupy
+except (ImportError, ModuleNotFoundError):
+    cupy = None
 
 
 @pytest.mark.gpu
 def test_storage():
-
     @dace.program
     def add(X: dace.float32[32, 32] @ StorageType.GPU_Global):
         return X + 1
@@ -46,7 +49,6 @@ def add2(X: dace.float32[32, 32] @ StorageType.GPU_Global):
 
 @pytest.mark.gpu
 def test_pythonmode():
-
     def runs_on_gpu(a: dace.float64[20] @ StorageType.GPU_Global, b: dace.float64[20] @ StorageType.GPU_Global):
         # This map will become a GPU kernel
         for i in dace.map[0:20] @ ScheduleType.GPU_Device:
@@ -58,7 +60,40 @@ def runs_on_gpu(a: dace.float64[20] @ StorageType.GPU_Global, b: dace.float64[20
     assert cupy.allclose(gpu_b, gpu_a + 1)
 
 
+def test_inline_storage_hint():
+    N = dace.symbol('N')
+
+    @dace.program
+    def tester():
+        b = np.ones(N, dtype=np.float32) @ dace.StorageType.CPU_ThreadLocal
+        return b + 1
+
+    sdfg = tester.to_sdfg(simplify=False)
+    assert sdfg.arrays['b'].storage == StorageType.CPU_ThreadLocal
+
+    b = tester(N=10)
+    assert np.allclose(b, 2)
+
+
+def test_annotated_storage_hint():
+    N = dace.symbol('N')
+
+    @dace.program
+    def tester():
+        b: dace.float32[N] @ dace.StorageType.CPU_ThreadLocal = np.ones(N, dtype=np.float32)
+        return b + 1
+
+    sdfg = tester.to_sdfg(simplify=False)
+    assert sdfg.arrays['b'].storage == StorageType.CPU_ThreadLocal
+
+    b = tester(N=10)
+    assert np.allclose(b, 2)
+
+
 if __name__ == "__main__":
-    test_storage()
-    test_schedule()
-    test_pythonmode()
+    if cupy is not None:
+        test_storage()
+        test_schedule()
+        test_pythonmode()
+    test_inline_storage_hint()
+    test_annotated_storage_hint()
diff --git a/tests/sdfg/cycles_test.py b/tests/sdfg/cycles_test.py
index 480392ab2d..b01aec55fd 100644
--- a/tests/sdfg/cycles_test.py
+++ b/tests/sdfg/cycles_test.py
@@ -2,7 +2,7 @@
 import pytest
 
 import dace
-
+from dace.sdfg.validation import InvalidSDFGError
 
 def test_cycles():
     with pytest.raises(ValueError, match="Found cycles.*"):
@@ -29,6 +29,23 @@ def test_cycles_memlet_path():
         sdfg.validate()
 
 
+def test_cycles_1562():
+    """
+    Test for issue #1562.
+    """
+    with pytest.raises(InvalidSDFGError, match="cycles"):
+        sdfg = dace.SDFG("foo")
+        state = sdfg.add_state()
+        mentry_2, mexit_2 = state.add_map("map_2", dict(i="0:9"))
+        mentry_6, mexit_6 = state.add_map("map_6", dict(i="0:9"))
+        mentry_8, mexit_8 = state.add_map("map_8", dict(i="0:9"))
+        state.add_edge(mentry_8, "OUT_0", mentry_6, "IN_0", dace.Memlet(data="bla", subset='0:9'))
+        state.add_edge(mentry_6, "OUT_0", mentry_2, "IN_0", dace.Memlet(data="bla", subset='0:9'))
+        state.add_edge(mentry_2, "OUT_0", mentry_6, "IN_0", dace.Memlet(data="bla", subset='0:9'))
+        sdfg.validate()
+
+
 if __name__ == '__main__':
     test_cycles()
     test_cycles_memlet_path()
+    test_cycles_1562()

From 1d8a693ef9a76af21b53e3a97c18cbf66b7ad92b Mon Sep 17 00:00:00 2001
From: Christos Kotsalos <kotsaloscv@gmail.com>
Date: Wed, 30 Oct 2024 06:31:02 +0100
Subject: [PATCH 03/33] infer_symbols_from_datadescriptor : modification to
 infer offset (#1525)

Small modification to infer offset on top of shape and strides from the
data descriptor (needed in gt4py)
---
 dace/frontend/python/parser.py | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/dace/frontend/python/parser.py b/dace/frontend/python/parser.py
index d99be1265d..d03759fa8e 100644
--- a/dace/frontend/python/parser.py
+++ b/dace/frontend/python/parser.py
@@ -92,14 +92,15 @@ def infer_symbols_from_datadescriptor(sdfg: SDFG,
             desc = sdfg.arrays[arg_name]
             if not hasattr(desc, 'shape') or not hasattr(arg_val, 'shape'):
                 continue
-            symbolic_values = list(desc.shape) + list(getattr(desc, 'strides', []))
+            symbolic_values = list(desc.shape) + list(getattr(desc, 'strides', [])) + list(getattr(desc, 'offset', []))
             given_values = list(arg_val.shape)
             given_strides = []
             if hasattr(arg_val, 'strides'):
                 # NumPy arrays use bytes in strides
                 factor = getattr(arg_val, 'itemsize', 1)
                 given_strides = [s // factor for s in arg_val.strides]
-            given_values += given_strides
+            given_offset = [o for o in arg_val.offset] if hasattr(arg_val, 'offset') else []
+            given_values += given_strides + given_offset
 
             for sym_dim, real_dim in zip(symbolic_values, given_values):
                 repldict = {}

From 3c164c44900a4b89685ff77105b6e63f2ed9759b Mon Sep 17 00:00:00 2001
From: Yakup Koray Budanaz <budanaz.yakup@gmail.com>
Date: Wed, 30 Oct 2024 06:31:49 +0100
Subject: [PATCH 04/33] Add CFG to generate_scope in tutorials (#1706)

The DFG is missing from codegen tutorial, resulting with an error in
codegen. Adding cfg as a param fixes it.
---
 tutorials/codegen.ipynb | 44 +++++++++++++++++++++--------------------
 1 file changed, 23 insertions(+), 21 deletions(-)

diff --git a/tutorials/codegen.ipynb b/tutorials/codegen.ipynb
index a6effd7996..2c79f1a2e0 100644
--- a/tutorials/codegen.ipynb
+++ b/tutorials/codegen.ipynb
@@ -480,48 +480,50 @@
     "        self.frame = frame_codegen\n",
     "        # Can be used to dispatch other code generators for allocation/nodes\n",
     "        self.dispatcher = frame_codegen.dispatcher\n",
-    "        \n",
+    "\n",
     "        ################################################################\n",
-    "        # Register handlers/hooks through dispatcher: Can be used for \n",
+    "        # Register handlers/hooks through dispatcher: Can be used for\n",
     "        # nodes, memory copy/allocation, scopes, states, and more.\n",
-    "        \n",
+    "\n",
     "        # In this case, register scopes\n",
     "        self.dispatcher.register_map_dispatcher(dace.ScheduleType.LoopyLoop, self)\n",
-    "        \n",
+    "\n",
     "        # You can similarly use register_{array,copy,node,state}_dispatcher\n",
-    "        \n",
-    "    # A scope dispatcher will trigger a method called generate_scope whenever \n",
+    "\n",
+    "    # A scope dispatcher will trigger a method called generate_scope whenever\n",
     "    # an SDFG has a scope with that schedule\n",
-    "    def generate_scope(self, sdfg: dace.SDFG, scope: ScopeSubgraphView,\n",
-    "                       state_id: int, function_stream: CodeIOStream,\n",
-    "                       callsite_stream: CodeIOStream):\n",
+    "    def generate_scope(self, sdfg: dace.SDFG, cfg: dace.ControlFlowRegion,\n",
+    "                       scope: ScopeSubgraphView, state_id: int,\n",
+    "                       function_stream: CodeIOStream, callsite_stream: CodeIOStream):\n",
     "        # The parameters here are:\n",
     "        # sdfg: The SDFG we are currently generating.\n",
+    "        # cfg: The current control flow graph (CFG) we are currently generating. For example,
+    "               it can be the SDFG or a loop region.
     "        # scope: The subgraph of the state containing only the scope (map contents)\n",
     "        #        we want to generate the code for.\n",
-    "        # state_id: The state in the SDFG the subgraph is taken from (i.e., \n",
+    "        # state_id: The state in the SDFG the subgraph is taken from (i.e.,\n",
     "        #           `sdfg.node(state_id)` is the same as `scope.graph`)\n",
     "        # function_stream: A cursor to the global code (which can be used to define\n",
     "        #                  functions, hence the name).\n",
     "        # callsite_stream: A cursor to the current location in the code, most of\n",
     "        #                  the code is generated here.\n",
-    "        \n",
+    "\n",
     "        # We can get the map entry node from the scope graph\n",
     "        entry_node = scope.source_nodes()[0]\n",
-    "        \n",
+    "\n",
     "        # First, generate an opening brace (for instrumentation and dynamic map ranges)\n",
     "        callsite_stream.write('{', sdfg, state_id, entry_node)\n",
-    "        \n",
+    "\n",
     "        ################################################################\n",
-    "        # Generate specific code: We will generate a reversed loop with a \n",
+    "        # Generate specific code: We will generate a reversed loop with a\n",
     "        # comment for each dimension of the map. For the sake of simplicity,\n",
     "        # dynamic map ranges are not supported.\n",
-    "        \n",
+    "\n",
     "        for param, rng in zip(entry_node.map.params, entry_node.map.range):\n",
     "            # We use the sym2cpp function from the cpp support functions\n",
     "            # to convert symbolic expressions to proper C++\n",
     "            begin, end, stride = (sym2cpp(r) for r in rng)\n",
-    "            \n",
+    "\n",
     "            # Every write is optionally (but recommended to be) tagged with\n",
     "            # 1-3 extra arguments, serving as line information to match\n",
     "            # SDFG, state, and graph nodes/edges to written code.\n",
@@ -529,17 +531,17 @@
     "            for (auto {param} = {end}; {param} >= {begin}; {param} -= {stride}) {{''',\n",
     "                                  sdfg, state_id, entry_node\n",
     "            )\n",
-    "        \n",
+    "\n",
     "            # NOTE: CodeIOStream will automatically take care of indentation for us.\n",
-    "        \n",
-    "        \n",
+    "\n",
+    "\n",
     "        # Now that the loops have been defined, use the dispatcher to invoke any\n",
     "        # code generator (including this one) that is registered to deal with\n",
     "        # the internal nodes in the subgraph. We skip the MapEntry node.\n",
-    "        self.dispatcher.dispatch_subgraph(sdfg, scope, state_id,\n",
+    "        self.dispatcher.dispatch_subgraph(sdfg, cfg, scope, state_id,\n",
     "                                          function_stream, callsite_stream,\n",
     "                                          skip_entry_node=True)\n",
-    "        \n",
+    "\n",
     "        # NOTE: Since skip_exit_node above is set to False, closing braces will\n",
     "        #       be automatically generated"
    ]

From 1343a6e6440d808644ffccd5937ae1fcb136b92e Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Philip=20M=C3=BCller?=
 <147368808+philip-paul-mueller@users.noreply.github.com>
Date: Wed, 30 Oct 2024 16:51:40 +0100
Subject: [PATCH 05/33] Better `CopyToMap` (#1675)

By default the transformation uses some linearization followed by a
delinearization approach, while this is needed to copy certain shapes,
it is unnecessarily complicated for memlets such as `a[0:10, 20:30] ->
40:50, 60:70`.
This PR adds special cases where the source and destination subset has
the same size and transforms it to a simple copy.
It also supports the case where some dimensions are one, i.e. memlets
such as `a[0:10, 0:10] -> 0:10, 1, 0:20`.

For all cases tests were added.
Most importantly the transformation now applies if the strides are the
same.
Before this case was blocked.

This PR helps to _avoid_ errors that are related to
[Issue#1674](https://github.com/spcl/dace/issues/1674), but it is not a
fix or a solution to it.
---
 dace/transformation/dataflow/copy_to_map.py |  90 ++++++++---
 tests/transformations/copy_to_map_test.py   | 164 +++++++++++++++++++-
 2 files changed, 229 insertions(+), 25 deletions(-)

diff --git a/dace/transformation/dataflow/copy_to_map.py b/dace/transformation/dataflow/copy_to_map.py
index 5b4260ad55..9c4dbce627 100644
--- a/dace/transformation/dataflow/copy_to_map.py
+++ b/dace/transformation/dataflow/copy_to_map.py
@@ -1,12 +1,13 @@
 # Copyright 2019-2022 ETH Zurich and the DaCe authors. All rights reserved.
 
-from dace import dtypes, symbolic, data, subsets, Memlet
+from dace import dtypes, symbolic, data, subsets, Memlet, properties
 from dace.sdfg.scope import is_devicelevel_gpu
 from dace.transformation import transformation as xf
 from dace.sdfg import SDFGState, SDFG, nodes, utils as sdutil
 from typing import Tuple
+import itertools
 
-
+@properties.make_properties
 class CopyToMap(xf.SingleStateTransformation):
     """
     Converts an access node -> access node copy into a map. Useful for generating manual code and
@@ -14,6 +15,10 @@ class CopyToMap(xf.SingleStateTransformation):
     """
     a = xf.PatternNode(nodes.AccessNode)
     b = xf.PatternNode(nodes.AccessNode)
+    ignore_strides = properties.Property(
+            default=False,
+            desc='Ignore the stride of the data container; Defaults to `False`.',
+    )
 
     @classmethod
     def expressions(cls):
@@ -31,7 +36,10 @@ def can_be_applied(self, graph: SDFGState, expr_index: int, sdfg: SDFG, permissi
         if isinstance(self.b.desc(sdfg), data.View):
             if sdutil.get_view_node(graph, self.b) == self.a:
                 return False
-        if self.a.desc(sdfg).strides == self.b.desc(sdfg).strides:
+        if (not self.ignore_strides) and self.a.desc(sdfg).strides == self.b.desc(sdfg).strides:
+            return False
+        # Ensures that the edge goes from `a` -> `b`.
+        if not any(edge.dst is self.b for edge in graph.out_edges(self.a)):
             return False
 
         return True
@@ -62,31 +70,69 @@ def delinearize_linearize(self, desc: data.Array, copy_shape: Tuple[symbolic.Sym
         return subsets.Range([(ind, ind, 1) for ind in cur_index])
 
     def apply(self, state: SDFGState, sdfg: SDFG):
-        adesc = self.a.desc(sdfg)
-        bdesc = self.b.desc(sdfg)
-        edge = state.edges_between(self.a, self.b)[0]
+        avnode = self.a
+        av = avnode.data
+        adesc = avnode.desc(sdfg)
+        bvnode = self.b
+        bv = bvnode.data
+        bdesc = bvnode.desc(sdfg)
+
+        edge = state.edges_between(avnode, bvnode)[0]
+        src_subset = edge.data.get_src_subset(edge, state)
+        if src_subset is None:
+            src_subset = subsets.Range.from_array(adesc)
+        src_subset_size = src_subset.size()
+        red_src_subset_size = tuple(s for s in src_subset_size if s != 1)
+
+        dst_subset = edge.data.get_dst_subset(edge, state)
+        if dst_subset is None:
+            dst_subset = subsets.Range.from_array(bdesc)
+        dst_subset_size = dst_subset.size()
+        red_dst_subset_size = tuple(s for s in dst_subset_size if s != 1)
 
         if len(adesc.shape) >= len(bdesc.shape):
-            copy_shape = edge.data.get_src_subset(edge, state).size()
+            copy_shape = src_subset_size
             copy_a = True
         else:
-            copy_shape = edge.data.get_dst_subset(edge, state).size()
+            copy_shape = dst_subset_size
             copy_a = False
 
-        maprange = {f'__i{i}': (0, s - 1, 1) for i, s in enumerate(copy_shape)}
-
-        av = self.a.data
-        bv = self.b.data
-        avnode = self.a
-        bvnode = self.b
-
-        # Linearize and delinearize to get index expression for other side
-        if copy_a:
-            a_index = [symbolic.pystr_to_symbolic(f'__i{i}') for i in range(len(copy_shape))]
-            b_index = self.delinearize_linearize(bdesc, copy_shape, edge.data.get_dst_subset(edge, state))
+        if tuple(src_subset_size) == tuple(dst_subset_size):
+            # The two subsets have exactly the same shape, so we can just copying with an offset.
+            #  We use another index variables for the tests only.
+            maprange = {f'__j{i}': (0, s - 1, 1) for i, s in enumerate(copy_shape)}
+            a_index = [symbolic.pystr_to_symbolic(f'__j{i} + ({src_subset[i][0]})') for i in range(len(copy_shape))]
+            b_index = [symbolic.pystr_to_symbolic(f'__j{i} + ({dst_subset[i][0]})') for i in range(len(copy_shape))]
+        elif red_src_subset_size == red_dst_subset_size and (len(red_dst_subset_size) > 0):
+            # If we remove all size 1 dimensions that the two subsets have the same size.
+            #  This is essentially the memlet `a[0:10, 2, 0:10] -> 0:10, 10:20`
+            #  We use another index variable only for the tests but we would have to
+            #  recreate the index anyways.
+            maprange = {f'__j{i}': (0, s - 1, 1) for i, s in enumerate(red_src_subset_size)}
+            cnt = itertools.count(0)
+            a_index = [
+                symbolic.pystr_to_symbolic(f'{src_subset[i][0]}')
+                if s == 1
+                else symbolic.pystr_to_symbolic(f'__j{next(cnt)} + ({src_subset[i][0]})')
+                for i, s in enumerate(src_subset_size)
+            ]
+            cnt = itertools.count(0)
+            b_index = [
+                symbolic.pystr_to_symbolic(f'{dst_subset[i][0]}')
+                if s == 1
+                else symbolic.pystr_to_symbolic(f'__j{next(cnt)} + ({dst_subset[i][0]})')
+                for i, s in enumerate(dst_subset_size)
+            ]
         else:
-            a_index = self.delinearize_linearize(adesc, copy_shape, edge.data.get_src_subset(edge, state))
-            b_index = [symbolic.pystr_to_symbolic(f'__i{i}') for i in range(len(copy_shape))]
+            # We have to delinearize and linearize
+            #  We use another index variable for the tests.
+            maprange = {f'__i{i}': (0, s - 1, 1) for i, s in enumerate(copy_shape)}
+            if copy_a:
+                a_index = [symbolic.pystr_to_symbolic(f'__i{i}') for i in range(len(copy_shape))]
+                b_index = self.delinearize_linearize(bdesc, copy_shape, edge.data.get_dst_subset(edge, state))
+            else:
+                a_index = self.delinearize_linearize(adesc, copy_shape, edge.data.get_src_subset(edge, state))
+                b_index = [symbolic.pystr_to_symbolic(f'__i{i}') for i in range(len(copy_shape))]
 
         a_subset = subsets.Range([(ind, ind, 1) for ind in a_index])
         b_subset = subsets.Range([(ind, ind, 1) for ind in b_index])
@@ -101,7 +147,7 @@ def apply(self, state: SDFGState, sdfg: SDFG):
                 schedule = dtypes.ScheduleType.GPU_Device
 
         # Add copy map
-        t, _, _ = state.add_mapped_tasklet('copy',
+        t, _, _ = state.add_mapped_tasklet(f'copy_{av}_{bv}',
                                            maprange,
                                            dict(__inp=Memlet(data=av, subset=a_subset)),
                                            '__out = __inp',
diff --git a/tests/transformations/copy_to_map_test.py b/tests/transformations/copy_to_map_test.py
index 2b237d84d5..a0931fa1b8 100644
--- a/tests/transformations/copy_to_map_test.py
+++ b/tests/transformations/copy_to_map_test.py
@@ -4,6 +4,8 @@
 import copy
 import pytest
 import numpy as np
+import re
+from typing import Tuple, Optional
 
 
 def _copy_to_map(storage: dace.StorageType):
@@ -102,9 +104,165 @@ def test_preprocess():
     assert np.allclose(out, inp)
 
 
+def _perform_non_lin_delin_test(
+        sdfg: dace.SDFG,
+) -> bool:
+    """Performs test for the special case CopyToMap that bypasses linearizing and delinearaziong.
+    """
+    assert sdfg.number_of_nodes() == 1
+    state: dace.SDFGState = sdfg.states()[0]
+    assert state.number_of_nodes() == 2
+    assert state.number_of_edges() == 1
+    assert all(isinstance(node, dace.nodes.AccessNode) for node in state.nodes())
+    sdfg.validate()
+
+    a = np.random.rand(*sdfg.arrays["a"].shape)
+    b_unopt = np.random.rand(*sdfg.arrays["b"].shape)
+    b_opt = b_unopt.copy()
+    sdfg(a=a, b=b_unopt)
+
+    nb_runs = sdfg.apply_transformations_repeated(CopyToMap, validate=True, options={"ignore_strides": True})
+    assert nb_runs == 1, f"Expected 1 application, but {nb_runs} were performed."
+
+    # Now looking for the tasklet and checking if the memlets follows the expected
+    #  simple pattern.
+    tasklet: dace.nodes.Tasklet = next(iter([node for node in state.nodes() if isinstance(node, dace.nodes.Tasklet)]))
+    pattern: re.Pattern = re.compile(r"(__j[0-9])|(__j[0-9]+\s*\+\s*[0-9]+)|([0-9]+)")
+
+    assert state.in_degree(tasklet) == 1
+    assert state.out_degree(tasklet) == 1
+    in_edge = next(iter(state.in_edges(tasklet)))
+    out_edge = next(iter(state.out_edges(tasklet)))
+
+    assert all(pattern.fullmatch(str(idxs[0]).strip()) for idxs in in_edge.data.src_subset), f"IN: {in_edge.data.src_subset}"
+    assert all(pattern.fullmatch(str(idxs[0]).strip()) for idxs in out_edge.data.dst_subset), f"OUT: {out_edge.data.dst_subset}"
+
+    # Now call it again after the optimization.
+    sdfg(a=a, b=b_opt)
+    assert np.allclose(b_unopt, b_opt)
+
+    return True
+
+def _make_non_lin_delin_sdfg(
+        shape_a: Tuple[int, ...],
+        shape_b: Optional[Tuple[int, ...]] = None
+) -> Tuple[dace.SDFG, dace.SDFGState, dace.nodes.AccessNode, dace.nodes.AccessNode]:
+
+    if shape_b is None:
+        shape_b = shape_a
+
+    sdfg = dace.SDFG("bypass1")
+    state = sdfg.add_state(is_start_block=True)
+
+    ac = []
+    for name, shape in [('a', shape_a), ('b', shape_b)]:
+        sdfg.add_array(
+                name=name,
+                shape=shape,
+                dtype=dace.float64,
+                transient=False,
+        )
+        ac.append(state.add_access(name))
+
+    return sdfg, state, ac[0], ac[1]
+
+
+def test_non_lin_delin_1():
+    sdfg, state, a, b = _make_non_lin_delin_sdfg((10, 10))
+    state.add_nedge(
+            a,
+            b,
+            dace.Memlet("a[0:10, 0:10] -> [0:10, 0:10]"),
+    )
+    _perform_non_lin_delin_test(sdfg)
+
+def test_non_lin_delin_2():
+    sdfg, state, a, b = _make_non_lin_delin_sdfg((10, 10), (100, 100))
+    state.add_nedge(
+            a,
+            b,
+            dace.Memlet("a[0:10, 0:10] -> [50:60, 40:50]"),
+    )
+    _perform_non_lin_delin_test(sdfg)
+
+
+def test_non_lin_delin_3():
+    sdfg, state, a, b = _make_non_lin_delin_sdfg((100, 100), (100, 100))
+    state.add_nedge(
+            a,
+            b,
+            dace.Memlet("a[1:11, 20:30] -> [50:60, 40:50]"),
+    )
+    _perform_non_lin_delin_test(sdfg)
+
+
+def test_non_lin_delin_4():
+    sdfg, state, a, b = _make_non_lin_delin_sdfg((100, 4, 100), (100, 100))
+    state.add_nedge(
+            a,
+            b,
+            dace.Memlet("a[1:11, 2, 20:30] -> [50:60, 40:50]"),
+    )
+    _perform_non_lin_delin_test(sdfg)
+
+
+def test_non_lin_delin_5():
+    sdfg, state, a, b = _make_non_lin_delin_sdfg((100, 4, 100), (100, 10, 100))
+    state.add_nedge(
+            a,
+            b,
+            dace.Memlet("a[1:11, 2, 20:30] -> [50:60, 4, 40:50]"),
+    )
+    _perform_non_lin_delin_test(sdfg)
+
+
+def test_non_lin_delin_6():
+    sdfg, state, a, b = _make_non_lin_delin_sdfg((100, 100), (100, 10, 100))
+    state.add_nedge(
+            a,
+            b,
+            dace.Memlet("a[1:11, 20:30] -> [50:60, 4, 40:50]"),
+    )
+    _perform_non_lin_delin_test(sdfg)
+
+
+def test_non_lin_delin_7():
+    sdfg, state, a, b = _make_non_lin_delin_sdfg((10, 10), (20, 20))
+    state.add_nedge(
+            a,
+            b,
+            dace.Memlet("b[5:15, 6:16]"),
+    )
+    _perform_non_lin_delin_test(sdfg)
+
+
+def test_non_lin_delin_8():
+    sdfg, state, a, b = _make_non_lin_delin_sdfg((20, 20), (10, 10))
+    state.add_nedge(
+            a,
+            b,
+            dace.Memlet("a[5:15, 6:16]"),
+    )
+    _perform_non_lin_delin_test(sdfg)
+
+
 if __name__ == '__main__':
+    test_non_lin_delin_1()
+    test_non_lin_delin_2()
+    test_non_lin_delin_3()
+    test_non_lin_delin_4()
+    test_non_lin_delin_5()
+    test_non_lin_delin_6()
+    test_non_lin_delin_7()
+    test_non_lin_delin_8()
+
     test_copy_to_map()
-    test_copy_to_map_gpu()
     test_flatten_to_map()
-    test_flatten_to_map_gpu()
-    test_preprocess()
+    try:
+        import cupy
+        test_copy_to_map_gpu()
+        test_flatten_to_map_gpu()
+        test_preprocess()
+    except ModuleNotFoundError as E:
+        if "'cupy'" not in str(E):
+            raise

From 2811e40486f8ed6c21f348abfa93747b8edd6215 Mon Sep 17 00:00:00 2001
From: Tal Ben-Nun <tbennun@users.noreply.github.com>
Date: Wed, 30 Oct 2024 12:12:38 -0700
Subject: [PATCH 06/33] More NumPy operation implementations (#1498)

* Concatenation and stacking (numpy.concatenate, numpy.stack, and
their variants)
* numpy.linspace
* Fix nested attribute parsing (Fixes #1295)
* numpy.clip
* numpy.split and its variants
* numpy.full variants (zeros, ones, etc.) with a single value for
shape (`np.zeros(N)`)
* NumPy-compatible numpy.arange dtype inference
* `numpy.fft.{fft, ifft}`
---
 dace/codegen/cppunparse.py                  |   8 +-
 dace/distr_types.py                         |   4 +
 dace/frontend/common/distr.py               |  32 +-
 dace/frontend/python/newast.py              |  57 +-
 dace/frontend/python/preprocessing.py       |   2 +
 dace/frontend/python/replacements.py        | 641 ++++++++++++++++++--
 dace/libraries/blas/nodes/gemv.py           |  16 +-
 dace/libraries/fft/__init__.py              |   6 +
 dace/libraries/fft/algorithms/__init__.py   |   0
 dace/libraries/fft/algorithms/dft.py        |  45 ++
 dace/libraries/fft/environments/__init__.py |   2 +
 dace/libraries/fft/environments/cufft.py    |  21 +
 dace/libraries/fft/nodes/__init__.py        |   2 +
 dace/libraries/fft/nodes/fft.py             | 204 +++++++
 dace/libraries/standard/nodes/transpose.py  |  31 +-
 tests/library/fft_test.py                   | 101 +++
 tests/numpy/array_creation_test.py          |  42 ++
 tests/numpy/attention_simple_test.py        |   2 +-
 tests/numpy/attribute_test.py               |  43 ++
 tests/numpy/concat_test.py                  | 133 ++++
 tests/numpy/nested_call_subarray_test.py    |   4 +-
 tests/numpy/split_test.py                   | 142 +++++
 tests/numpy/ufunc_test.py                   |   6 +
 23 files changed, 1458 insertions(+), 86 deletions(-)
 create mode 100644 dace/libraries/fft/__init__.py
 create mode 100644 dace/libraries/fft/algorithms/__init__.py
 create mode 100644 dace/libraries/fft/algorithms/dft.py
 create mode 100644 dace/libraries/fft/environments/__init__.py
 create mode 100644 dace/libraries/fft/environments/cufft.py
 create mode 100644 dace/libraries/fft/nodes/__init__.py
 create mode 100644 dace/libraries/fft/nodes/fft.py
 create mode 100644 tests/library/fft_test.py
 create mode 100644 tests/numpy/concat_test.py
 create mode 100644 tests/numpy/split_test.py

diff --git a/dace/codegen/cppunparse.py b/dace/codegen/cppunparse.py
index 18ee00721b..edeb5270ca 100644
--- a/dace/codegen/cppunparse.py
+++ b/dace/codegen/cppunparse.py
@@ -749,6 +749,8 @@ def _Num(self, t):
         # For complex values, use ``dtype_to_typeclass``
         if isinstance(t_n, complex):
             dtype = dtypes.dtype_to_typeclass(complex)
+            repr_n = f'{dtype}({t_n.real}, {t_n.imag})'
+
 
         # Handle large integer values
         if isinstance(t_n, int):
@@ -765,10 +767,8 @@ def _Num(self, t):
             elif bits >= 64:
                 warnings.warn(f'Value wider than 64 bits encountered in expression ({t_n}), emitting as-is')
 
-        if repr_n.endswith("j"):
-            self.write("%s(0, %s)" % (dtype, repr_n.replace("inf", INFSTR)[:-1]))
-        else:
-            self.write(repr_n.replace("inf", INFSTR))
+        repr_n = repr_n.replace("inf", INFSTR)
+        self.write(repr_n)
 
     def _List(self, t):
         raise NotImplementedError('Invalid C++')
diff --git a/dace/distr_types.py b/dace/distr_types.py
index 1b595a1b84..b60eb4925e 100644
--- a/dace/distr_types.py
+++ b/dace/distr_types.py
@@ -96,6 +96,10 @@ def _validate(self):
             raise ValueError('Color must have only logical true (1) or false (0) values.')
         return True
 
+    @property
+    def dtype(self):
+        return type(self)
+
     def to_json(self):
         attrs = serialize.all_properties_to_json(self)
         retdict = {"type": type(self).__name__, "attributes": attrs}
diff --git a/dace/frontend/common/distr.py b/dace/frontend/common/distr.py
index 88a6b0c54a..c517028d53 100644
--- a/dace/frontend/common/distr.py
+++ b/dace/frontend/common/distr.py
@@ -50,14 +50,14 @@ def _cart_create(pv: 'ProgramVisitor', sdfg: SDFG, state: SDFGState, dims: Shape
 
 
 @oprepo.replaces_method('Intracomm', 'Create_cart')
-def _intracomm_create(pv: 'ProgramVisitor', sdfg: SDFG, state: SDFGState, icomm: 'Intracomm', dims: ShapeType):
+def _intracomm_create(pv: 'ProgramVisitor', sdfg: SDFG, state: SDFGState, icomm: str, dims: ShapeType):
     """ Equivalent to `dace.comm.Cart_create(dims).
         :param dims: Shape of the process-grid (see `dims` parameter of `MPI_Cart_create`), e.g., [2, 3, 3].
         :return: Name of the new process-grid descriptor.
     """
 
     from mpi4py import MPI
-    icomm_name, icomm_obj = icomm
+    icomm_name, icomm_obj = icomm, pv.globals[icomm]
     if icomm_obj != MPI.COMM_WORLD:
         raise ValueError('Only the mpi4py.MPI.COMM_WORLD Intracomm is supported in DaCe Python programs.')
     return _cart_create(pv, sdfg, state, dims)
@@ -186,13 +186,13 @@ def _bcast(pv: ProgramVisitor,
 def _intracomm_bcast(pv: 'ProgramVisitor',
                      sdfg: SDFG,
                      state: SDFGState,
-                     comm: Tuple[str, 'Comm'],
+                     comm: str,
                      buffer: str,
                      root: Union[str, sp.Expr, Number] = 0):
     """ Equivalent to `dace.comm.Bcast(buffer, root)`. """
 
     from mpi4py import MPI
-    comm_name, comm_obj = comm
+    comm_name, comm_obj = comm, pv.globals[comm]
     if comm_obj == MPI.COMM_WORLD:
         return _bcast(pv, sdfg, state, buffer, root)
     # NOTE: Highly experimental
@@ -267,12 +267,12 @@ def _alltoall(pv: 'ProgramVisitor', sdfg: SDFG, state: SDFGState, inbuffer: str,
 
 
 @oprepo.replaces_method('Intracomm', 'Alltoall')
-def _intracomm_alltoall(pv: 'ProgramVisitor', sdfg: SDFG, state: SDFGState, icomm: 'Intracomm', inp_buffer: str,
+def _intracomm_alltoall(pv: 'ProgramVisitor', sdfg: SDFG, state: SDFGState, icomm: str, inp_buffer: str,
                         out_buffer: str):
     """ Equivalent to `dace.comm.Alltoall(inp_buffer, out_buffer)`. """
 
     from mpi4py import MPI
-    icomm_name, icomm_obj = icomm
+    icomm_name, icomm_obj = icomm, pv.globals[icomm]
     if icomm_obj != MPI.COMM_WORLD:
         raise ValueError('Only the mpi4py.MPI.COMM_WORLD Intracomm is supported in DaCe Python programs.')
     return _alltoall(pv, sdfg, state, inp_buffer, out_buffer)
@@ -303,12 +303,12 @@ def _allreduce(pv: ProgramVisitor, sdfg: SDFG, state: SDFGState, buffer: str, op
 
 
 @oprepo.replaces_method('Intracomm', 'Allreduce')
-def _intracomm_allreduce(pv: 'ProgramVisitor', sdfg: SDFG, state: SDFGState, icomm: 'Intracomm', inp_buffer: 'InPlace',
+def _intracomm_allreduce(pv: 'ProgramVisitor', sdfg: SDFG, state: SDFGState, icomm: str, inp_buffer: 'InPlace',
                          out_buffer: str, op: str):
     """ Equivalent to `dace.comm.Allreduce(out_buffer, op)`. """
 
     from mpi4py import MPI
-    icomm_name, icomm_obj = icomm
+    icomm_name, icomm_obj = icomm, pv.globals[icomm]
     if icomm_obj != MPI.COMM_WORLD:
         raise ValueError('Only the mpi4py.MPI.COMM_WORLD Intracomm is supported in DaCe Python programs.')
     if inp_buffer != MPI.IN_PLACE:
@@ -470,12 +470,12 @@ def _send(pv: ProgramVisitor,
 
 
 @oprepo.replaces_method('Intracomm', 'Send')
-def _intracomm_send(pv: 'ProgramVisitor', sdfg: SDFG, state: SDFGState, icomm: 'Intracomm', buffer: str,
+def _intracomm_send(pv: 'ProgramVisitor', sdfg: SDFG, state: SDFGState, icomm: str, buffer: str,
                     dst: Union[str, sp.Expr, Number], tag: Union[str, sp.Expr, Number]):
     """ Equivalent to `dace.comm.end(buffer, dst, tag)`. """
 
     from mpi4py import MPI
-    icomm_name, icomm_obj = icomm
+    icomm_name, icomm_obj = icomm, pv.globals[icomm]
     if icomm_obj != MPI.COMM_WORLD:
         raise ValueError('Only the mpi4py.MPI.COMM_WORLD Intracomm is supported in DaCe Python programs.')
     return _send(pv, sdfg, state, buffer, dst, tag)
@@ -592,12 +592,12 @@ def _isend(pv: ProgramVisitor,
 
 
 @oprepo.replaces_method('Intracomm', 'Isend')
-def _intracomm_isend(pv: 'ProgramVisitor', sdfg: SDFG, state: SDFGState, icomm: 'Intracomm', buffer: str,
+def _intracomm_isend(pv: 'ProgramVisitor', sdfg: SDFG, state: SDFGState, icomm: str, buffer: str,
                      dst: Union[str, sp.Expr, Number], tag: Union[str, sp.Expr, Number]):
     """ Equivalent to `dace.comm.Isend(buffer, dst, tag, req)`. """
 
     from mpi4py import MPI
-    icomm_name, icomm_obj = icomm
+    icomm_name, icomm_obj = icomm, pv.globals[icomm]
     if icomm_obj != MPI.COMM_WORLD:
         raise ValueError('Only the mpi4py.MPI.COMM_WORLD Intracomm is supported in DaCe Python programs.')
     req, _ = sdfg.add_array("isend_req", [1], dace.dtypes.opaque("MPI_Request"), transient=True, find_new_name=True)
@@ -690,12 +690,12 @@ def _recv(pv: ProgramVisitor,
 
 
 @oprepo.replaces_method('Intracomm', 'Recv')
-def _intracomm_Recv(pv: 'ProgramVisitor', sdfg: SDFG, state: SDFGState, icomm: 'Intracomm', buffer: str,
+def _intracomm_Recv(pv: 'ProgramVisitor', sdfg: SDFG, state: SDFGState, icomm: str, buffer: str,
                     src: Union[str, sp.Expr, Number], tag: Union[str, sp.Expr, Number]):
     """ Equivalent to `dace.comm.Recv(buffer, src, tagq)`. """
 
     from mpi4py import MPI
-    icomm_name, icomm_obj = icomm
+    icomm_name, icomm_obj = icomm, pv.globals[icomm]
     if icomm_obj != MPI.COMM_WORLD:
         raise ValueError('Only the mpi4py.MPI.COMM_WORLD Intracomm is supported in DaCe Python programs.')
     return _recv(pv, sdfg, state, buffer, src, tag)
@@ -810,12 +810,12 @@ def _irecv(pv: ProgramVisitor,
 
 
 @oprepo.replaces_method('Intracomm', 'Irecv')
-def _intracomm_irecv(pv: 'ProgramVisitor', sdfg: SDFG, state: SDFGState, icomm: 'Intracomm', buffer: str,
+def _intracomm_irecv(pv: 'ProgramVisitor', sdfg: SDFG, state: SDFGState, icomm: str, buffer: str,
                      src: Union[str, sp.Expr, Number], tag: Union[str, sp.Expr, Number]):
     """ Equivalent to `dace.comm.Irecv(buffer, src, tag, req)`. """
 
     from mpi4py import MPI
-    icomm_name, icomm_obj = icomm
+    icomm_name, icomm_obj = icomm, pv.globals[icomm]
     if icomm_obj != MPI.COMM_WORLD:
         raise ValueError('Only the mpi4py.MPI.COMM_WORLD Intracomm is supported in DaCe Python programs.')
     req, _ = sdfg.add_array("irecv_req", [1], dace.dtypes.opaque("MPI_Request"), transient=True, find_new_name=True)
diff --git a/dace/frontend/python/newast.py b/dace/frontend/python/newast.py
index 78890c9cdd..b4e83cc1e7 100644
--- a/dace/frontend/python/newast.py
+++ b/dace/frontend/python/newast.py
@@ -1342,7 +1342,7 @@ def defined(self):
 
         # MPI-related stuff
         result.update({
-            k: self.sdfg.process_grids[v]
+            v: self.sdfg.process_grids[v]
             for k, v in self.variables.items() if v in self.sdfg.process_grids
         })
         try:
@@ -4461,7 +4461,14 @@ def visit_Call(self, node: ast.Call, create_callbacks=False):
                 func = node.func.value
 
         if func is None:
-            funcname = rname(node)
+            func_result = self.visit(node.func)
+            if isinstance(func_result, str):
+                if isinstance(node.func, ast.Attribute):
+                    funcname = f'{func_result}.{node.func.attr}'
+                else:
+                    funcname = func_result
+            else:
+                funcname = rname(node)
             # Check if the function exists as an SDFG in a different module
             modname = until(funcname, '.')
             if ('.' in funcname and len(modname) > 0 and modname in self.globals
@@ -4576,7 +4583,7 @@ def visit_Call(self, node: ast.Call, create_callbacks=False):
                 arg = self.scope_vars[modname]
             else:
                 # Fallback to (name, object)
-                arg = (modname, self.defined[modname])
+                arg = modname
             args.append(arg)
         # Otherwise, try to find a default implementation for the SDFG
         elif not found_ufunc:
@@ -4795,12 +4802,18 @@ def _visitname(self, name: str, node: ast.AST):
                 self.sdfg.add_symbol(result.name, result.dtype)
             return result
 
+        if name in self.closure.callbacks:
+            return name
+
         if name in self.sdfg.arrays:
             return name
 
         if name in self.sdfg.symbols:
             return name
 
+        if name in __builtins__:
+            return name
+
         if name not in self.scope_vars:
             raise DaceSyntaxError(self, node, 'Use of undefined variable "%s"' % name)
         rname = self.scope_vars[name]
@@ -4845,33 +4858,43 @@ def visit_NameConstant(self, node: NameConstant):
         return self.visit_Constant(node)
 
     def visit_Attribute(self, node: ast.Attribute):
-        # If visiting an attribute, return attribute value if it's of an array or global
-        name = until(astutils.unparse(node), '.')
-        result = self._visitname(name, node)
+        result = self.visit(node.value)
+        if isinstance(result, (tuple, list, dict)):
+            if len(result) > 1:
+                raise DaceSyntaxError(
+                    self, node.value, f'{type(result)} object cannot use attributes. Try storing the '
+                    'object to a different variable first (e.g., ``a = result; a.attribute``')
+            else:
+                result = result[0]
+
         tmpname = f"{result}.{astutils.unparse(node.attr)}"
         if tmpname in self.sdfg.arrays:
             return tmpname
+
         if isinstance(result, str) and result in self.sdfg.arrays:
             arr = self.sdfg.arrays[result]
         elif isinstance(result, str) and result in self.scope_arrays:
             arr = self.scope_arrays[result]
         else:
-            return result
+            arr = None
 
         # Try to find sub-SDFG attribute
-        func = oprepo.Replacements.get_attribute(type(arr), node.attr)
-        if func is not None:
-            # A new state is likely needed here, e.g., for transposition (ndarray.T)
-            self._add_state('%s_%d' % (type(node).__name__, node.lineno))
-            self.last_block.set_default_lineinfo(self.current_lineinfo)
-            result = func(self, self.sdfg, self.last_block, result)
-            self.last_block.set_default_lineinfo(None)
-            return result
+        if arr is not None:
+            func = oprepo.Replacements.get_attribute(type(arr), node.attr)
+            if func is not None:
+                # A new state is likely needed here, e.g., for transposition (ndarray.T)
+                self._add_state('%s_%d' % (type(node).__name__, node.lineno))
+                self.last_block.set_default_lineinfo(self.current_lineinfo)
+                result = func(self, self.sdfg, self.last_block, result)
+                self.last_block.set_default_lineinfo(None)
+                return result
 
         # Otherwise, try to find compile-time attribute (such as shape)
         try:
-            return getattr(arr, node.attr)
-        except KeyError:
+            if arr is not None:
+                return getattr(arr, node.attr)
+            return getattr(result, node.attr)
+        except (AttributeError, KeyError):
             return result
 
     def visit_List(self, node: ast.List):
diff --git a/dace/frontend/python/preprocessing.py b/dace/frontend/python/preprocessing.py
index eca07a4930..f51b67ddb2 100644
--- a/dace/frontend/python/preprocessing.py
+++ b/dace/frontend/python/preprocessing.py
@@ -527,6 +527,8 @@ def global_value_to_node(self,
         elif isinstance(value, symbolic.symbol):
             # Symbols resolve to the symbol name
             newnode = ast.Name(id=value.name, ctx=ast.Load())
+        elif isinstance(value, sympy.Basic):  # Symbolic or constant expression
+            newnode = ast.parse(symbolic.symstr(value)).body[0].value
         elif isinstance(value, ast.Name):
             newnode = ast.Name(id=value.id, ctx=ast.Load())
         elif (dtypes.isconstant(value) or isinstance(value, (StringLiteral, SDFG)) or hasattr(value, '__sdfg__')):
diff --git a/dace/frontend/python/replacements.py b/dace/frontend/python/replacements.py
index 537fef97bf..c5b3e3b2a2 100644
--- a/dace/frontend/python/replacements.py
+++ b/dace/frontend/python/replacements.py
@@ -313,6 +313,9 @@ def _numpy_full(pv: ProgramVisitor,
     """ Creates and array of the specified shape and initializes it with
         the fill value.
     """
+    if isinstance(shape, Number) or symbolic.issymbolic(shape):
+        shape = [shape]
+    
     is_data = False
     if isinstance(fill_value, (Number, np.bool_)):
         vtype = dtypes.dtype_to_typeclass(type(fill_value))
@@ -548,8 +551,13 @@ def _numpy_rot90(pv: ProgramVisitor, sdfg: SDFG, state: SDFGState, arr: str, k=1
 
 @oprepo.replaces('numpy.arange')
 @oprepo.replaces('dace.arange')
-def _arange(pv: ProgramVisitor, sdfg: SDFG, state: SDFGState, *args, **kwargs):
-    """ Implementes numpy.arange """
+def _arange(pv: ProgramVisitor,
+            sdfg: SDFG,
+            state: SDFGState,
+            *args,
+            dtype: dtypes.typeclass = None,
+            like: Optional[str] = None):
+    """ Implements numpy.arange """
 
     start = 0
     stop = None
@@ -563,35 +571,42 @@ def _arange(pv: ProgramVisitor, sdfg: SDFG, state: SDFGState, *args, **kwargs):
     else:
         start, stop, step = args
 
+    if isinstance(start, str):
+        raise TypeError(f'Cannot compile numpy.arange with a scalar start value "{start}" (only constants and symbolic '
+                        'expressions are supported). Please use numpy.linspace instead.')
+    if isinstance(stop, str):
+        raise TypeError(f'Cannot compile numpy.arange with a scalar stop value "{stop}" (only constants and symbolic '
+                        'expressions are supported). Please use numpy.linspace instead.')
+    if isinstance(step, str):
+        raise TypeError(f'Cannot compile numpy.arange with a scalar step value "{step}" (only constants and symbolic '
+                        'expressions are supported). Please use numpy.linspace instead.')
+
     actual_step = step
     if isinstance(start, Number) and isinstance(stop, Number):
         actual_step = type(start + step)(start + step) - start
 
     if any(not isinstance(s, Number) for s in [start, stop, step]):
-        shape = (symbolic.int_ceil(stop - start, step), )
+        if step == 1:  # Common case where ceiling is not necessary
+            shape = (stop - start,)
+        else:
+            shape = (symbolic.int_ceil(stop - start, step), )
     else:
         shape = (np.int64(np.ceil((stop - start) / step)), )
 
-    if not isinstance(shape[0], Number) and ('dtype' not in kwargs or kwargs['dtype'] == None):
-        raise NotImplementedError("The current implementation of numpy.arange requires that the output dtype is given "
-                                  "when at least one of (start, stop, step) is symbolic.")
+    # Infer dtype from input arguments
+    if dtype is None:
+        dtype, _ = _result_type(args)
+
     # TODO: Unclear what 'like' does
-    # if 'like' in kwargs and kwargs['like'] != None:
-    #     outname, outarr = sdfg.add_temp_transient_like(sdfg.arrays[kwargs['like']])
+    # if like is not None:
+    #     outname, outarr = sdfg.add_temp_transient_like(sdfg.arrays[like])
     #     outarr.shape = shape
-    if 'dtype' in kwargs and kwargs['dtype'] != None:
-        dtype = kwargs['dtype']
-        if not isinstance(dtype, dtypes.typeclass):
-            dtype = dtypes.dtype_to_typeclass(dtype)
-        outname, outarr = sdfg.add_temp_transient(shape, dtype)
-    else:
-        # infer dtype based on args's dtype
-        # (since the `dtype` keyword argument isn't given, none of the arguments can be symbolic)
-        if any(isinstance(arg, (float, np.float32, np.float64)) for arg in args):
-            dtype = dtypes.float64
-        else:
-            dtype = dtypes.int64
-        outname, outarr = sdfg.add_temp_transient(shape, dtype)
+    if not isinstance(dtype, dtypes.typeclass):
+        dtype = dtypes.dtype_to_typeclass(dtype)
+    outname, outarr = sdfg.add_temp_transient(shape, dtype)
+
+    start = f'decltype(__out)({start})'
+    actual_step = f'decltype(__out)({actual_step})'
 
     state.add_mapped_tasklet(name="_numpy_arange_",
                              map_ranges={'__i': f"0:{shape[0]}"},
@@ -603,6 +618,131 @@ def _arange(pv: ProgramVisitor, sdfg: SDFG, state: SDFGState, *args, **kwargs):
     return outname
 
 
+def _add_axis_to_shape(shape: Sequence[symbolic.SymbolicType], axis: int,
+                       axis_value: Any) -> List[symbolic.SymbolicType]:
+    if axis > len(shape):
+        raise ValueError(f'axis {axis} is out of bounds for array of dimension {len(shape)}')
+    if axis < 0:
+        naxis = len(shape) + 1 + axis
+        if naxis < 0 or naxis > len(shape):
+            raise ValueError(f'axis {axis} is out of bounds for array of dimension {len(shape)}')
+        axis = naxis
+
+    # Make a new shape list with the inserted dimension
+    new_shape = [None] * (len(shape) + 1)
+    for i in range(len(shape) + 1):
+        if i == axis:
+            new_shape[i] = axis_value
+        elif i < axis:
+            new_shape[i] = shape[i]
+        else:
+            new_shape[i] = shape[i - 1]
+
+    return new_shape
+
+
+@oprepo.replaces('numpy.linspace')
+def _linspace(pv: ProgramVisitor,
+              sdfg: SDFG,
+              state: SDFGState,
+              start: Union[Number, symbolic.SymbolicType, str],
+              stop: Union[Number, symbolic.SymbolicType, str],
+              num: Union[Integral, symbolic.SymbolicType] = 50,
+              endpoint: bool = True,
+              retstep: bool = False,
+              dtype: dtypes.typeclass = None,
+              axis: int = 0):
+    """ Implements numpy.linspace """
+    # Argument checks
+    if not isinstance(num, (Integral, sp.Basic)):
+        raise TypeError('numpy.linspace can only be compiled when the ``num`` argument is symbolic or constant.')
+    if not isinstance(axis, Integral):
+        raise TypeError('numpy.linspace can only be compiled when the ``axis`` argument is constant.')
+
+    # Start and stop are broadcast together, then, a new dimension is added to axis (taken from ``ndim + 1``),
+    # along which the numbers are filled.
+    start_shape = sdfg.arrays[start].shape if (isinstance(start, str) and start in sdfg.arrays) else []
+    stop_shape = sdfg.arrays[stop].shape if (isinstance(stop, str) and stop in sdfg.arrays) else []
+
+    shape, ranges, outind, ind1, ind2 = _broadcast_together(start_shape, stop_shape)
+    shape_with_axis = _add_axis_to_shape(shape, axis, num)
+    ranges_with_axis = _add_axis_to_shape(ranges, axis, ('__sind', f'0:{symbolic.symstr(num)}'))
+    if outind:
+        outind_with_axis = _add_axis_to_shape(outind.split(', '), axis, '__sind')
+    else:
+        outind_with_axis = ['__sind']
+
+    if dtype is None:
+        # Infer output type from start and stop
+        start_type = sdfg.arrays[start] if (isinstance(start, str) and start in sdfg.arrays) else start
+        stop_type = sdfg.arrays[stop] if (isinstance(stop, str) and stop in sdfg.arrays) else stop
+
+        dtype, _ = _result_type((start_type, stop_type), 'Add')
+
+        # From the NumPy documentation: The inferred dtype will never be an integer; float is chosen even if the
+        # arguments would produce an array of integers.
+        if dtype in (dtypes.int8, dtypes.int16, dtypes.int32, dtypes.int64, dtypes.uint8, dtypes.uint16, dtypes.uint32,
+                     dtypes.uint64):
+            dtype = dtypes.dtype_to_typeclass(float)
+
+    outname, _ = sdfg.add_temp_transient(shape_with_axis, dtype)
+
+    if endpoint == True:
+        num -= 1
+
+    # Fill in input memlets as necessary
+    inputs = {}
+    if isinstance(start, str) and start in sdfg.arrays:
+        index = f'[{ind1}]' if ind1 else ''
+        inputs['__start'] = Memlet(f'{start}{index}')
+        startcode = '__start'
+    else:
+        startcode = symbolic.symstr(start)
+
+    if isinstance(stop, str) and stop in sdfg.arrays:
+        index = f'[{ind2}]' if ind2 else ''
+        inputs['__stop'] = Memlet(f'{stop}{index}')
+        stopcode = '__stop'
+    else:
+        stopcode = symbolic.symstr(stop)
+
+    # Create tasklet code based on inputs
+    code = f'__out = {startcode} + __sind * decltype(__out)({stopcode} - {startcode}) / decltype(__out)({symbolic.symstr(num)})'
+
+    state.add_mapped_tasklet(name="linspace",
+                             map_ranges=ranges_with_axis,
+                             inputs=inputs,
+                             code=code,
+                             outputs={'__out': Memlet(f"{outname}[{','.join(outind_with_axis)}]")},
+                             external_edges=True)
+
+    if retstep == False:
+        return outname
+
+    # Return step if requested
+
+    # Handle scalar outputs
+    if not ranges:
+        ranges = [('__unused', '0:1')]
+    out_index = f'[{outind}]'
+
+    if len(shape) > 0:
+        stepname, _ = sdfg.add_temp_transient(shape, dtype)
+    else:
+        stepname, _ = sdfg.add_scalar(sdfg.temp_data_name(), dtype, transient=True)
+        out_index = '[0]'
+
+    state.add_mapped_tasklet(
+        'retstep',
+        ranges,
+        copy.deepcopy(inputs),
+        f'__out = decltype(__out)({stopcode} - {startcode}) / decltype(__out)({symbolic.symstr(num)})',
+        {'__out': Memlet(f"{stepname}{out_index}")},
+        external_edges=True)
+
+    return outname, stepname
+
+
 @oprepo.replaces('elementwise')
 @oprepo.replaces('dace.elementwise')
 def _elementwise(pv: 'ProgramVisitor',
@@ -708,9 +848,9 @@ def _simple_call(sdfg: SDFG, state: SDFGState, inpname: str, func: str, restype:
 
 
 def _complex_to_scalar(complex_type: dace.typeclass):
-    if complex_type is dace.complex64:
+    if complex_type == dace.complex64:
         return dace.float32
-    elif complex_type is dace.complex128:
+    elif complex_type == dace.complex128:
         return dace.float64
     else:
         return complex_type
@@ -814,7 +954,8 @@ def _len_array(pv: 'ProgramVisitor', sdfg: SDFG, state: SDFGState, a: str):
             return sdfg.arrays[a].shape[0]
         if a in sdfg.constants_prop:
             return len(sdfg.constants[a])
-    raise TypeError(f'`len` is not supported for input "{a}" (type {type(a)})')
+    else:
+        return len(a)
 
 
 @oprepo.replaces('transpose')
@@ -1632,8 +1773,17 @@ def _result_type(arguments: Sequence[Union[str, Number, symbolic.symbol, sp.Basi
 
     else:  # Operators with 3 or more arguments
         result_type = _np_result_type(dtypes_for_result)
+        coarse_result_type = None
+        if result_type in complex_types:
+            coarse_result_type = 3  # complex
+        elif result_type in float_types:
+            coarse_result_type = 2  # float
+        elif result_type in signed_types:
+            coarse_result_type = 1  # signed integer, bool
+        else:
+            coarse_result_type = 0  # unsigned integer
         for i, t in enumerate(coarse_types):
-            if t != result_type:
+            if t != coarse_result_type:
                 casting[i] = _cast_str(result_type)
 
     return result_type, casting
@@ -2512,6 +2662,13 @@ def _matmult(visitor: ProgramVisitor, sdfg: SDFG, state: SDFGState, op1: str, op
                code="__out = log1p(__in1)",
                reduce=None,
                initial=np.log1p.identity),
+    clip=dict(name="_numpy_clip_",
+              operator=None,
+              inputs=["__in_a", "__in_amin", "__in_amax"],
+              outputs=["__out"],
+              code="__out = min(max(__in_a, __in_amin), __in_amax)",
+              reduce=None,
+              initial=np.inf),
     sqrt=dict(name="_numpy_sqrt_",
               operator="Sqrt",
               inputs=["__in1"],
@@ -4087,14 +4244,13 @@ def implement_ufunc_outer(visitor: ProgramVisitor, ast_node: ast.Call, sdfg: SDF
 
 
 @oprepo.replaces('numpy.reshape')
-def reshape(
-    pv: ProgramVisitor,
-    sdfg: SDFG,
-    state: SDFGState,
-    arr: str,
-    newshape: Union[str, symbolic.SymbolicType, Tuple[Union[str, symbolic.SymbolicType]]],
-    order: StringLiteral = StringLiteral('C')
-) -> str:
+def reshape(pv: ProgramVisitor,
+            sdfg: SDFG,
+            state: SDFGState,
+            arr: str,
+            newshape: Union[str, symbolic.SymbolicType, Tuple[Union[str, symbolic.SymbolicType]]],
+            order: StringLiteral = StringLiteral('C'),
+            strides: Optional[Any] = None) -> str:
     if isinstance(arr, (list, tuple)) and len(arr) == 1:
         arr = arr[0]
     desc = sdfg.arrays[arr]
@@ -4108,10 +4264,11 @@ def reshape(
 
     # New shape and strides as symbolic expressions
     newshape = [symbolic.pystr_to_symbolic(s) for s in newshape]
-    if fortran_strides:
-        strides = [data._prod(newshape[:i]) for i in range(len(newshape))]
-    else:
-        strides = [data._prod(newshape[i + 1:]) for i in range(len(newshape))]
+    if strides is None:
+        if fortran_strides:
+            strides = [data._prod(newshape[:i]) for i in range(len(newshape))]
+        else:
+            strides = [data._prod(newshape[i + 1:]) for i in range(len(newshape))]
 
     newarr, newdesc = sdfg.add_view(arr,
                                     newshape,
@@ -4326,9 +4483,13 @@ def _ndarray_reshape(
     sdfg: SDFG,
     state: SDFGState,
     arr: str,
-    newshape: Union[str, symbolic.SymbolicType, Tuple[Union[str, symbolic.SymbolicType]]],
+    *newshape: Union[str, symbolic.SymbolicType, Tuple[Union[str, symbolic.SymbolicType]]],
     order: StringLiteral = StringLiteral('C')
 ) -> str:
+    if len(newshape) == 0:
+        raise TypeError('reshape() takes at least 1 argument (0 given)')
+    if len(newshape) == 1 and isinstance(newshape, (list, tuple)):
+        newshape = newshape[0]
     return reshape(pv, sdfg, state, arr, newshape, order)
 
 
@@ -4833,3 +4994,407 @@ def _op(visitor: 'ProgramVisitor', sdfg: SDFG, state: SDFGState, op1: StringLite
 
 for op, method in _boolop_to_method.items():
     _makeboolop(op, method)
+
+
+@oprepo.replaces('numpy.concatenate')
+def _concat(visitor: ProgramVisitor,
+            sdfg: SDFG,
+            state: SDFGState,
+            arrays: Tuple[Any],
+            axis: Optional[int] = 0,
+            out: Optional[Any] = None,
+            *,
+            dtype=None,
+            casting: str = 'same_kind'):
+    if dtype is not None and out is not None:
+        raise ValueError('Arguments dtype and out cannot be given together')
+    if casting != 'same_kind':
+        raise NotImplementedError('The casting argument is currently unsupported')
+    if not isinstance(arrays, (tuple, list)):
+        raise ValueError('List of arrays is not iterable, cannot compile concatenation')
+    if axis is not None and not isinstance(axis, Integral):
+        raise ValueError('Axis is not a compile-time evaluatable integer, cannot compile concatenation')
+    if len(arrays) == 1:
+        return arrays[0]
+    for i in range(len(arrays)):
+        if arrays[i] not in sdfg.arrays:
+            raise TypeError(f'Index {i} is not an array')
+    if out is not None:
+        if out not in sdfg.arrays:
+            raise TypeError('Output is not an array')
+        dtype = sdfg.arrays[out].dtype
+
+    descs = [sdfg.arrays[arr] for arr in arrays]
+    shape = list(descs[0].shape)
+
+    if axis is None:  # Flatten arrays, then concatenate
+        arrays = [flat(visitor, sdfg, state, arr) for arr in arrays]
+        descs = [sdfg.arrays[arr] for arr in arrays]
+        shape = list(descs[0].shape)
+        axis = 0
+    else:
+        # Check shapes for validity
+        first_shape = copy.copy(shape)
+        first_shape[axis] = 0
+        for i, d in enumerate(descs[1:]):
+            other_shape = list(d.shape)
+            other_shape[axis] = 0
+            if other_shape != first_shape:
+                raise ValueError(f'Array shapes do not match at index {i}')
+
+    shape[axis] = sum(desc.shape[axis] for desc in descs)
+    if out is None:
+        if dtype is None:
+            dtype = descs[0].dtype
+        name, odesc = sdfg.add_temp_transient(shape, dtype, storage=descs[0].storage, lifetime=descs[0].lifetime)
+    else:
+        name = out
+        odesc = sdfg.arrays[out]
+
+    # Make copies
+    w = state.add_write(name)
+    offset = 0
+    subset = subsets.Range.from_array(odesc)
+    for arr, desc in zip(arrays, descs):
+        r = state.add_read(arr)
+        subset = copy.deepcopy(subset)
+        subset[axis] = (offset, offset + desc.shape[axis] - 1, 1)
+        state.add_edge(r, None, w, None, Memlet(data=name, subset=subset))
+        offset += desc.shape[axis]
+
+    return name
+
+
+@oprepo.replaces('numpy.stack')
+def _stack(visitor: ProgramVisitor,
+           sdfg: SDFG,
+           state: SDFGState,
+           arrays: Tuple[Any],
+           axis: int = 0,
+           out: Any = None,
+           *,
+           dtype=None,
+           casting: str = 'same_kind'):
+    if dtype is not None and out is not None:
+        raise ValueError('Arguments dtype and out cannot be given together')
+    if casting != 'same_kind':
+        raise NotImplementedError('The casting argument is currently unsupported')
+    if not isinstance(arrays, (tuple, list)):
+        raise ValueError('List of arrays is not iterable, cannot compile stack call')
+    if not isinstance(axis, Integral):
+        raise ValueError('Axis is not a compile-time evaluatable integer, cannot compile stack call')
+
+    for i in range(len(arrays)):
+        if arrays[i] not in sdfg.arrays:
+            raise TypeError(f'Index {i} is not an array')
+
+    descs = [sdfg.arrays[a] for a in arrays]
+    shape = descs[0].shape
+    for i, d in enumerate(descs[1:]):
+        if d.shape != shape:
+            raise ValueError(f'Array shapes are not equal ({shape} != {d.shape} at index {i})')
+
+    if axis > len(shape):
+        raise ValueError(f'axis {axis} is out of bounds for array of dimension {len(shape)}')
+    if axis < 0:
+        naxis = len(shape) + 1 + axis
+        if naxis < 0 or naxis > len(shape):
+            raise ValueError(f'axis {axis} is out of bounds for array of dimension {len(shape)}')
+        axis = naxis
+
+    # Stacking is implemented as a reshape followed by concatenation
+    reshaped = []
+    for arr, desc in zip(arrays, descs):
+        # Make a reshaped view with the inserted dimension
+        new_shape = [0] * (len(shape) + 1)
+        new_strides = [0] * (len(shape) + 1)
+        for i in range(len(shape) + 1):
+            if i == axis:
+                new_shape[i] = 1
+                new_strides[i] = desc.strides[i - 1] if i != 0 else desc.strides[i]
+            elif i < axis:
+                new_shape[i] = shape[i]
+                new_strides[i] = desc.strides[i]
+            else:
+                new_shape[i] = shape[i - 1]
+                new_strides[i] = desc.strides[i - 1]
+
+        rname = reshape(visitor, sdfg, state, arr, new_shape, strides=new_strides)
+        reshaped.append(rname)
+
+    return _concat(visitor, sdfg, state, reshaped, axis, out, dtype=dtype, casting=casting)
+
+
+@oprepo.replaces('numpy.vstack')
+@oprepo.replaces('numpy.row_stack')
+def _vstack(visitor: ProgramVisitor,
+            sdfg: SDFG,
+            state: SDFGState,
+            tup: Tuple[Any],
+            *,
+            dtype=None,
+            casting: str = 'same_kind'):
+    if not isinstance(tup, (tuple, list)):
+        raise ValueError('List of arrays is not iterable, cannot compile stack call')
+    if tup[0] not in sdfg.arrays:
+        raise TypeError(f'Index 0 is not an array')
+
+    # In the 1-D case, stacking is performed along the first axis
+    if len(sdfg.arrays[tup[0]].shape) == 1:
+        return _stack(visitor, sdfg, state, tup, axis=0, out=None, dtype=dtype, casting=casting)
+    # Otherwise, concatenation is performed
+    return _concat(visitor, sdfg, state, tup, axis=0, out=None, dtype=dtype, casting=casting)
+
+
+@oprepo.replaces('numpy.hstack')
+@oprepo.replaces('numpy.column_stack')
+def _hstack(visitor: ProgramVisitor,
+            sdfg: SDFG,
+            state: SDFGState,
+            tup: Tuple[Any],
+            *,
+            dtype=None,
+            casting: str = 'same_kind'):
+    if not isinstance(tup, (tuple, list)):
+        raise ValueError('List of arrays is not iterable, cannot compile stack call')
+    if tup[0] not in sdfg.arrays:
+        raise TypeError(f'Index 0 is not an array')
+
+    # In the 1-D case, concatenation is performed along the first axis
+    if len(sdfg.arrays[tup[0]].shape) == 1:
+        return _concat(visitor, sdfg, state, tup, axis=0, out=None, dtype=dtype, casting=casting)
+
+    return _concat(visitor, sdfg, state, tup, axis=1, out=None, dtype=dtype, casting=casting)
+
+
+@oprepo.replaces('numpy.dstack')
+def _dstack(visitor: ProgramVisitor,
+            sdfg: SDFG,
+            state: SDFGState,
+            tup: Tuple[Any],
+            *,
+            dtype=None,
+            casting: str = 'same_kind'):
+    if not isinstance(tup, (tuple, list)):
+        raise ValueError('List of arrays is not iterable, cannot compile a stack call')
+    if tup[0] not in sdfg.arrays:
+        raise TypeError(f'Index 0 is not an array')
+    if len(sdfg.arrays[tup[0]].shape) < 3:
+        raise NotImplementedError('dstack is not implemented for arrays that are smaller than 3D')
+
+    return _concat(visitor, sdfg, state, tup, axis=2, out=None, dtype=dtype, casting=casting)
+
+
+def _split_core(visitor: ProgramVisitor, sdfg: SDFG, state: SDFGState, ary: str,
+                indices_or_sections: Union[int, Sequence[symbolic.SymbolicType], str], axis: int, allow_uneven: bool):
+    # Argument checks
+    if not isinstance(ary, str) or ary not in sdfg.arrays:
+        raise TypeError('Split object must be an array')
+    if not isinstance(axis, Integral):
+        raise ValueError('Cannot determine split dimension, axis is not a compile-time evaluatable integer')
+
+    desc = sdfg.arrays[ary]
+
+    # Test validity of axis
+    orig_axis = axis
+    if axis < 0:
+        axis = len(desc.shape) + axis
+    if axis < 0 or axis >= len(desc.shape):
+        raise ValueError(f'axis {orig_axis} is out of bounds for array of dimension {len(desc.shape)}')
+
+    # indices_or_sections may only be an integer (not symbolic), list of integers, list of symbols, or an array
+    if isinstance(indices_or_sections, str):
+        raise ValueError('Array-indexed split cannot be compiled due to data-dependent sizes. '
+                         'Consider using numpy.reshape instead.')
+    elif isinstance(indices_or_sections, (list, tuple)):
+        if any(isinstance(i, str) for i in indices_or_sections):
+            raise ValueError('Array-indexed split cannot be compiled due to data-dependent sizes. '
+                             'Use symbolic values as an argument instead.')
+        # Sequence is given
+        sections = indices_or_sections
+    elif isinstance(indices_or_sections, Integral):  # Constant integer given
+        if indices_or_sections <= 0:
+            raise ValueError('Number of sections must be larger than zero.')
+
+        # If uneven sizes are not allowed and ary shape is numeric, check evenness
+        if not allow_uneven and not symbolic.issymbolic(desc.shape[axis]):
+            if desc.shape[axis] % indices_or_sections != 0:
+                raise ValueError('Array split does not result in an equal division. Consider using numpy.array_split '
+                                 'instead.')
+        if indices_or_sections > desc.shape[axis]:
+            raise ValueError('Cannot compile array split as it will result in empty arrays.')
+
+        # Sequence is not given, compute sections
+        # Mimic behavior of array_split in numpy: Sections are [s+1 x N%s], s, ..., s
+        size = desc.shape[axis] // indices_or_sections
+        remainder = desc.shape[axis] % indices_or_sections
+        sections = []
+        offset = 0
+        for _ in range(min(remainder, indices_or_sections)):
+            offset += size + 1
+            sections.append(offset)
+        for _ in range(remainder, indices_or_sections - 1):
+            offset += size
+            sections.append(offset)
+
+    elif symbolic.issymbolic(indices_or_sections):
+        raise ValueError('Symbolic split cannot be compiled due to output tuple size being unknown. '
+                         'Consider using numpy.reshape instead.')
+    else:
+        raise TypeError(f'Unsupported type {type(indices_or_sections)} for indices_or_sections in numpy.split')
+
+    # Split according to sections
+    r = state.add_read(ary)
+    result = []
+    offset = 0
+    for section in sections:
+        shape = list(desc.shape)
+        shape[axis] = section - offset
+        name, _ = sdfg.add_temp_transient(shape, desc.dtype, storage=desc.storage, lifetime=desc.lifetime)
+        # Add copy
+        w = state.add_write(name)
+        subset = subsets.Range.from_array(desc)
+        subset[axis] = (offset, offset + shape[axis] - 1, 1)
+        offset += shape[axis]
+        state.add_nedge(r, w, Memlet(data=ary, subset=subset))
+        result.append(name)
+
+    # Add final section
+    shape = list(desc.shape)
+    shape[axis] -= offset
+    name, _ = sdfg.add_temp_transient(shape, desc.dtype, storage=desc.storage, lifetime=desc.lifetime)
+    w = state.add_write(name)
+    subset = subsets.Range.from_array(desc)
+    subset[axis] = (offset, offset + shape[axis] - 1, 1)
+    state.add_nedge(r, w, Memlet(data=ary, subset=subset))
+    result.append(name)
+
+    # Always return a list of results, even if the size is 1
+    return result
+
+
+@oprepo.replaces('numpy.split')
+def _split(visitor: ProgramVisitor,
+           sdfg: SDFG,
+           state: SDFGState,
+           ary: str,
+           indices_or_sections: Union[symbolic.SymbolicType, List[symbolic.SymbolicType], str],
+           axis: int = 0):
+    return _split_core(visitor, sdfg, state, ary, indices_or_sections, axis, allow_uneven=False)
+
+
+@oprepo.replaces('numpy.array_split')
+def _array_split(visitor: ProgramVisitor,
+                 sdfg: SDFG,
+                 state: SDFGState,
+                 ary: str,
+                 indices_or_sections: Union[symbolic.SymbolicType, List[symbolic.SymbolicType], str],
+                 axis: int = 0):
+    return _split_core(visitor, sdfg, state, ary, indices_or_sections, axis, allow_uneven=True)
+
+
+@oprepo.replaces('numpy.dsplit')
+def _dsplit(visitor: ProgramVisitor, sdfg: SDFG, state: SDFGState, ary: str,
+            indices_or_sections: Union[symbolic.SymbolicType, List[symbolic.SymbolicType], str]):
+    if isinstance(ary, str) and ary in sdfg.arrays:
+        if len(sdfg.arrays[ary].shape) < 3:
+            raise ValueError('Array dimensionality must be 3 or above for dsplit')
+    return _split_core(visitor, sdfg, state, ary, indices_or_sections, axis=2, allow_uneven=False)
+
+
+@oprepo.replaces('numpy.hsplit')
+def _hsplit(visitor: ProgramVisitor, sdfg: SDFG, state: SDFGState, ary: str,
+            indices_or_sections: Union[symbolic.SymbolicType, List[symbolic.SymbolicType], str]):
+    if isinstance(ary, str) and ary in sdfg.arrays:
+        # In case of a 1D array, split with axis=0
+        if len(sdfg.arrays[ary].shape) <= 1:
+            return _split_core(visitor, sdfg, state, ary, indices_or_sections, axis=0, allow_uneven=False)
+    return _split_core(visitor, sdfg, state, ary, indices_or_sections, axis=1, allow_uneven=False)
+
+
+@oprepo.replaces('numpy.vsplit')
+def _vsplit(visitor: ProgramVisitor, sdfg: SDFG, state: SDFGState, ary: str,
+            indices_or_sections: Union[symbolic.SymbolicType, List[symbolic.SymbolicType], str]):
+    return _split_core(visitor, sdfg, state, ary, indices_or_sections, axis=0, allow_uneven=False)
+
+
+############################################################################################################
+# Fast Fourier Transform numpy package (numpy.fft)
+
+def _real_to_complex(real_type: dace.typeclass):
+    if real_type == dace.float32:
+        return dace.complex64
+    elif real_type == dace.float64:
+        return dace.complex128
+    else:
+        return real_type
+
+
+def _fft_core(pv: 'ProgramVisitor',
+              sdfg: SDFG,
+              state: SDFGState,
+              a: str,
+              n: Optional[dace.symbolic.SymbolicType] = None,
+              axis=-1,
+              norm: StringLiteral = StringLiteral('backward'),
+              is_inverse: bool = False):
+    from dace.libraries.fft.nodes import FFT, IFFT  # Avoid import loops
+    if axis != 0 and axis != -1:
+        raise NotImplementedError('Only one dimensional arrays are supported at the moment')
+    if not isinstance(a, str) or a not in sdfg.arrays:
+        raise ValueError('Input must be a valid array')
+
+    libnode = FFT('fft') if not is_inverse else IFFT('ifft')
+
+    desc = sdfg.arrays[a]
+    N = desc.shape[axis]
+
+    # If n is not None, either pad input or slice and add a view
+    if n is not None:
+        raise NotImplementedError
+
+    # Compute factor
+    if norm == 'forward':
+        factor = (1 / N) if not is_inverse else 1
+    elif norm == 'backward':
+        factor = 1 if not is_inverse else (1 / N)
+    elif norm == 'ortho':
+        factor = sp.sqrt(1 / N)
+    else:
+        raise ValueError('norm argument can only be one of "forward", "backward", or "ortho".')
+    libnode.factor = factor
+
+    # Compute output type from input type
+    if is_inverse and desc.dtype not in (dace.complex64, dace.complex128):
+        raise TypeError(f'Inverse FFT only accepts complex inputs, got {desc.dtype}')
+    dtype = _real_to_complex(desc.dtype)
+
+    name, odesc = sdfg.add_temp_transient_like(desc, dtype)
+    r = state.add_read(a)
+    w = state.add_write(name)
+    state.add_edge(r, None, libnode, '_inp', Memlet.from_array(a, desc))
+    state.add_edge(libnode, '_out', w, None, Memlet.from_array(name, odesc))
+
+    return name
+
+
+@oprepo.replaces('numpy.fft.fft')
+def _fft(pv: 'ProgramVisitor',
+         sdfg: SDFG,
+         state: SDFGState,
+         a: str,
+         n: Optional[dace.symbolic.SymbolicType] = None,
+         axis=-1,
+         norm: StringLiteral = StringLiteral('backward')):
+    return _fft_core(pv, sdfg, state, a, n, axis, norm, False)
+
+
+@oprepo.replaces('numpy.fft.ifft')
+def _ifft(pv: 'ProgramVisitor',
+          sdfg: SDFG,
+          state: SDFGState,
+          a,
+          n=None,
+          axis=-1,
+          norm: StringLiteral = StringLiteral('backward')):
+    return _fft_core(pv, sdfg, state, a, n, axis, norm, True)
diff --git a/dace/libraries/blas/nodes/gemv.py b/dace/libraries/blas/nodes/gemv.py
index baf6fb415d..52091c6864 100644
--- a/dace/libraries/blas/nodes/gemv.py
+++ b/dace/libraries/blas/nodes/gemv.py
@@ -730,6 +730,9 @@ def expansion(node: 'Gemv', state, sdfg, m=None, n=None, **kwargs):
         dtype_a = outer_array_a.dtype.type
         dtype = outer_array_x.dtype.base_type
         veclen = outer_array_x.dtype.veclen
+        alpha = f'{dtype.ctype}({node.alpha})'
+        beta = f'{dtype.ctype}({node.beta})'
+
         m = m or node.m
         n = n or node.n
         if m is None:
@@ -765,8 +768,17 @@ def expansion(node: 'Gemv', state, sdfg, m=None, n=None, **kwargs):
 
         func = func.lower() + 'gemv'
 
-        code = f"""cblas_{func}({layout}, {trans}, {m}, {n}, {node.alpha}, _A, {lda},
-                                _x, {strides_x[0]}, {node.beta}, _y, {strides_y[0]});"""
+        code = ''
+        if dtype in (dace.complex64, dace.complex128):
+            code = f'''
+            {dtype.ctype} __alpha = {alpha};
+            {dtype.ctype} __beta = {beta};
+            '''
+            alpha = '&__alpha'
+            beta = '&__beta'
+
+        code += f"""cblas_{func}({layout}, {trans}, {m}, {n}, {alpha}, _A, {lda},
+                                _x, {strides_x[0]}, {beta}, _y, {strides_y[0]});"""
 
         tasklet = dace.sdfg.nodes.Tasklet(node.name,
                                           node.in_connectors,
diff --git a/dace/libraries/fft/__init__.py b/dace/libraries/fft/__init__.py
new file mode 100644
index 0000000000..71fb014f32
--- /dev/null
+++ b/dace/libraries/fft/__init__.py
@@ -0,0 +1,6 @@
+# Copyright 2019-2024 ETH Zurich and the DaCe authors. All rights reserved.
+from dace.library import register_library
+from .nodes import *
+from .environments import *
+
+register_library(__name__, "fft")
diff --git a/dace/libraries/fft/algorithms/__init__.py b/dace/libraries/fft/algorithms/__init__.py
new file mode 100644
index 0000000000..e69de29bb2
diff --git a/dace/libraries/fft/algorithms/dft.py b/dace/libraries/fft/algorithms/dft.py
new file mode 100644
index 0000000000..340dfed22d
--- /dev/null
+++ b/dace/libraries/fft/algorithms/dft.py
@@ -0,0 +1,45 @@
+# Copyright 2019-2024 ETH Zurich and the DaCe authors. All rights reserved.
+"""
+One-dimensional Discrete Fourier Transform (DFT) native implementations.
+"""
+import dace
+import numpy as np
+import math
+
+
+# Native, naive version of the Discrete Fourier Transform
+@dace.program
+def dft(_inp, _out, N: dace.compiletime, factor: dace.compiletime):
+    i = np.arange(N)
+    e = np.exp(-2j * np.pi * i * i[:, None] / N)
+    _out[:] = factor * (e @ _inp.astype(dace.complex128))
+
+
+@dace.program
+def idft(_inp, _out, N: dace.compiletime, factor: dace.compiletime):
+    i = np.arange(N)
+    e = np.exp(2j * np.pi * i * i[:, None] / N)
+    _out[:] = factor * (e @ _inp.astype(dace.complex128))
+
+
+# Single-map version of DFT, useful for integrating small Fourier transforms into other operations
+@dace.program
+def dft_explicit(_inp, _out, N: dace.compiletime, factor: dace.compiletime):
+    _out[:] = 0
+    for i, n in dace.map[0:N, 0:N]:
+        with dace.tasklet:
+            inp << _inp[n]
+            exponent = 2 * math.pi * i * n / N
+            b = decltype(b)(math.cos(exponent), -math.sin(exponent)) * inp * factor
+            b >> _out(1, lambda a, b: a + b)[i]
+
+
+@dace.program
+def idft_explicit(_inp, _out, N: dace.compiletime, factor: dace.compiletime):
+    _out[:] = 0
+    for i, n in dace.map[0:N, 0:N]:
+        with dace.tasklet:
+            inp << _inp[n]
+            exponent = 2 * math.pi * i * n / N
+            b = decltype(b)(math.cos(exponent), math.sin(exponent)) * inp * factor
+            b >> _out(1, lambda a, b: a + b)[i]
diff --git a/dace/libraries/fft/environments/__init__.py b/dace/libraries/fft/environments/__init__.py
new file mode 100644
index 0000000000..0900214e68
--- /dev/null
+++ b/dace/libraries/fft/environments/__init__.py
@@ -0,0 +1,2 @@
+# Copyright 2019-2024 ETH Zurich and the DaCe authors. All rights reserved.
+from .cufft import *
diff --git a/dace/libraries/fft/environments/cufft.py b/dace/libraries/fft/environments/cufft.py
new file mode 100644
index 0000000000..dd243d376a
--- /dev/null
+++ b/dace/libraries/fft/environments/cufft.py
@@ -0,0 +1,21 @@
+# Copyright 2019-2024 ETH Zurich and the DaCe authors. All rights reserved.
+import dace.library
+
+
+@dace.library.environment
+class cuFFT:
+
+    cmake_minimum_version = None
+    cmake_packages = ["CUDA"]
+    cmake_variables = {}
+    cmake_includes = []
+    cmake_libraries = ["cufft"]
+    cmake_compile_flags = []
+    cmake_link_flags = []
+    cmake_files = []
+
+    headers = {'frame': ["cufft.h", "cufftXt.h"], 'cuda': ["cufft.h", "cufftXt.h"]}
+    state_fields = []
+    init_code = ""
+    finalize_code = ""
+    dependencies = []
diff --git a/dace/libraries/fft/nodes/__init__.py b/dace/libraries/fft/nodes/__init__.py
new file mode 100644
index 0000000000..dd8f132aa4
--- /dev/null
+++ b/dace/libraries/fft/nodes/__init__.py
@@ -0,0 +1,2 @@
+# Copyright 2019-2024 ETH Zurich and the DaCe authors. All rights reserved.
+from .fft import FFT, IFFT
diff --git a/dace/libraries/fft/nodes/fft.py b/dace/libraries/fft/nodes/fft.py
new file mode 100644
index 0000000000..bc85f8785b
--- /dev/null
+++ b/dace/libraries/fft/nodes/fft.py
@@ -0,0 +1,204 @@
+# Copyright 2019-2024 ETH Zurich and the DaCe authors. All rights reserved.
+"""
+Implements Forward and Inverse Fast Fourier Transform (FFT) library nodes
+"""
+import warnings
+
+from dace import data, dtypes, SDFG, SDFGState, symbolic, library, nodes, properties
+from dace import transformation as xf
+from dace.libraries.fft import environments as env
+
+
+# Define the library nodes
+@library.node
+class FFT(nodes.LibraryNode):
+    implementations = {}
+    default_implementation = 'pure'
+
+    factor = properties.SymbolicProperty(desc='Coefficient to multiply outputs. Used for normalization', default=1.0)
+
+    def __init__(self, name, *args, schedule=None, **kwargs):
+        super().__init__(name, *args, schedule=schedule, inputs={'_inp'}, outputs={'_out'}, **kwargs)
+
+
+@library.node
+class IFFT(nodes.LibraryNode):
+    implementations = {}
+    default_implementation = 'pure'
+
+    factor = properties.SymbolicProperty(desc='Coefficient to multiply outputs. Used for normalization', default=1.0)
+
+    def __init__(self, name, *args, schedule=None, **kwargs):
+        super().__init__(name, *args, schedule=schedule, inputs={'_inp'}, outputs={'_out'}, **kwargs)
+
+
+##################################################################################################
+# Native SDFG expansions
+##################################################################################################
+
+
+@library.register_expansion(FFT, 'pure')
+class DFTExpansion(xf.ExpandTransformation):
+    environments = []
+
+    @staticmethod
+    def expansion(node: FFT, parent_state: SDFGState, parent_sdfg: SDFG) -> SDFG:
+        from dace.libraries.fft.algorithms import dft  # Lazy import functions
+        input, output = _get_input_and_output(parent_state, node)
+        indesc = parent_sdfg.arrays[input]
+        outdesc = parent_sdfg.arrays[output]
+        if len(indesc.shape) != 1:
+            raise NotImplementedError('Native SDFG expansion for FFT does not yet support N-dimensional inputs')
+
+        warnings.warn('Performance Warning: No assumptions on FFT input size, falling back to DFT')
+        return dft.dft_explicit.to_sdfg(indesc, outdesc, N=indesc.shape[0], factor=node.factor)
+
+
+@library.register_expansion(IFFT, 'pure')
+class IDFTExpansion(xf.ExpandTransformation):
+    environments = []
+
+    @staticmethod
+    def expansion(node: IFFT, parent_state: SDFGState, parent_sdfg: SDFG) -> SDFG:
+        from dace.libraries.fft.algorithms import dft  # Lazy import functions
+        input, output = _get_input_and_output(parent_state, node)
+        indesc = parent_sdfg.arrays[input]
+        outdesc = parent_sdfg.arrays[output]
+        if len(indesc.shape) != 1:
+            raise NotImplementedError('Native SDFG expansion for IFFT does not yet support N-dimensional inputs')
+
+        warnings.warn('Performance Warning: No assumptions on IFFT input size, falling back to DFT')
+        return dft.idft_explicit.to_sdfg(indesc, outdesc, N=indesc.shape[0], factor=node.factor)
+
+
+##################################################################################################
+# cuFFT expansions
+##################################################################################################
+
+
+@library.register_expansion(FFT, 'cuFFT')
+class cuFFTFFTExpansion(xf.ExpandTransformation):
+    environments = [env.cuFFT]
+    plan_uid = 0
+
+    @staticmethod
+    def expansion(node: FFT, parent_state: SDFGState, parent_sdfg: SDFG) -> SDFG:
+        input, output = _get_input_and_output(parent_state, node)
+        indesc = parent_sdfg.arrays[input]
+        outdesc = parent_sdfg.arrays[output]
+        if str(node.factor) != '1':
+            raise NotImplementedError('Multiplicative post-FFT factors are not yet implemented')
+        return _generate_cufft_code(indesc, outdesc, parent_sdfg, False)
+
+
+@library.register_expansion(IFFT, 'cuFFT')
+class cuFFTIFFTExpansion(xf.ExpandTransformation):
+    environments = [env.cuFFT]
+    plan_uid = 0
+
+    @staticmethod
+    def expansion(node: IFFT, parent_state: SDFGState, parent_sdfg: SDFG) -> SDFG:
+        input, output = _get_input_and_output(parent_state, node)
+        indesc = parent_sdfg.arrays[input]
+        outdesc = parent_sdfg.arrays[output]
+        if str(node.factor) != '1':
+            raise NotImplementedError('Multiplicative post-FFT factors are not yet implemented')
+        return _generate_cufft_code(indesc, outdesc, parent_sdfg, True)
+
+
+def _generate_cufft_code(indesc: data.Data, outdesc: data.Data, sdfg: SDFG, is_inverse: bool):
+    from dace.codegen.targets import cpp  # Avoid import loops
+    if len(indesc.shape) not in (1, 2, 3):
+        raise ValueError('cuFFT only supports 1/2/3-dimensional FFT')
+    if indesc.storage != dtypes.StorageType.GPU_Global:
+        raise ValueError('cuFFT implementation requires input array to be on GPU')
+    if outdesc.storage != dtypes.StorageType.GPU_Global:
+        raise ValueError('cuFFT implementation requires output array to be on GPU')
+
+    cufft_type = _types_to_cufft(indesc.dtype, outdesc.dtype)
+    init_code = ''
+    exit_code = ''
+    callsite_code = ''
+
+    # Make a unique name for this plan
+    if not is_inverse:
+        plan_name = f'fwdplan{cuFFTFFTExpansion.plan_uid}'
+        cuFFTFFTExpansion.plan_uid += 1
+        direction = 'CUFFT_FORWARD'
+        tasklet_prefix = ''
+    else:
+        plan_name = f'invplan{cuFFTIFFTExpansion.plan_uid}'
+        cuFFTIFFTExpansion.plan_uid += 1
+        direction = 'CUFFT_INVERSE'
+        tasklet_prefix = 'i'
+
+    fields = [
+        f'cufftHandle {plan_name};',
+    ]
+    plan_name = f'__state->{plan_name}'
+
+    init_code += f'''
+    cufftCreate(&{plan_name});
+    '''
+    exit_code += f'''
+    cufftDestroy({plan_name});
+    '''
+
+    cdims = ', '.join([cpp.sym2cpp(s) for s in indesc.shape])
+    make_plan = f'''
+    {{
+        size_t __work_size = 0;
+        cufftMakePlan{len(indesc.shape)}d({plan_name}, {cdims}, {cufft_type}, /*batch=*/1, &__work_size);
+    }}
+    '''
+
+    # Make plan in init if not symbolic or not data-dependent, otherwise make at callsite.
+    symbols_that_change = set(s for ise in sdfg.edges() for s in ise.data.assignments.keys())
+    symbols_that_change &= set(map(str, sdfg.symbols.keys()))
+
+    def _fsyms(x):
+        if symbolic.issymbolic(x):
+            return set(map(str, x.free_symbols))
+        return set()
+
+    if symbols_that_change and any(_fsyms(s) & symbols_that_change for s in indesc.shape):
+        callsite_code += make_plan
+    else:
+        init_code += make_plan
+
+    # Execute plan
+    callsite_code += f'''
+    cufftSetStream({plan_name}, __dace_current_stream);
+    cufftXtExec({plan_name}, _inp, _out, {direction});
+    '''
+
+    return nodes.Tasklet(f'cufft_{tasklet_prefix}fft', {'_inp'}, {'_out'},
+                         callsite_code,
+                         language=dtypes.Language.CPP,
+                         state_fields=fields,
+                         code_init=init_code,
+                         code_exit=exit_code)
+
+
+##################################################################################################
+# Helper functions
+##################################################################################################
+
+
+def _get_input_and_output(state: SDFGState, node: nodes.LibraryNode):
+    """
+    Helper function that returns the input and output arrays of the library node
+    """
+    in_edge = next(e for e in state.in_edges(node) if e.dst_conn)
+    out_edge = next(e for e in state.out_edges(node) if e.src_conn)
+    return in_edge.data.data, out_edge.data.data
+
+
+def _types_to_cufft(indtype: dtypes.typeclass, outdtype: dtypes.typeclass):
+    typedict = {
+        dtypes.float32: 'R',
+        dtypes.float64: 'D',
+        dtypes.complex64: 'C',
+        dtypes.complex128: 'Z',
+    }
+    return f'CUFFT_{typedict[indtype]}2{typedict[outdtype]}'
diff --git a/dace/libraries/standard/nodes/transpose.py b/dace/libraries/standard/nodes/transpose.py
index 58c6cfc33e..e2795ef951 100644
--- a/dace/libraries/standard/nodes/transpose.py
+++ b/dace/libraries/standard/nodes/transpose.py
@@ -100,6 +100,12 @@ class ExpandTransposeMKL(ExpandTransformation):
     @staticmethod
     def expansion(node, state, sdfg):
         node.validate(sdfg, state)
+
+        # Fall back to native implementation if input and output types are not the same
+        if (sdfg.arrays[list(state.in_edges_by_connector(node, '_inp'))[0].data.data].dtype != sdfg.arrays[list(
+                state.out_edges_by_connector(node, '_out'))[0].data.data].dtype):
+            return ExpandTransposePure.make_sdfg(node, state, sdfg)
+
         dtype = node.dtype
         if dtype == dace.float32:
             func = "somatcopy"
@@ -141,22 +147,30 @@ class ExpandTransposeOpenBLAS(ExpandTransformation):
     @staticmethod
     def expansion(node, state, sdfg):
         node.validate(sdfg, state)
+
+        # Fall back to native implementation if input and output types are not the same
+        if (sdfg.arrays[list(state.in_edges_by_connector(node, '_inp'))[0].data.data].dtype != sdfg.arrays[list(
+                state.out_edges_by_connector(node, '_out'))[0].data.data].dtype):
+            return ExpandTransposePure.make_sdfg(node, state, sdfg)
+
         dtype = node.dtype
         cast = ""
         if dtype == dace.float32:
             func = "somatcopy"
             alpha = "1.0f"
+            cast = ''
         elif dtype == dace.float64:
             func = "domatcopy"
             alpha = "1.0"
+            cast = ''
         elif dtype == dace.complex64:
             func = "comatcopy"
-            cast = "(float*)"
-            alpha = f"{cast}dace::blas::BlasConstants::Get().Complex64Pone()"
+            alpha = "dace::blas::BlasConstants::Get().Complex64Pone()"
+            cast = '(float*)'
         elif dtype == dace.complex128:
             func = "zomatcopy"
-            cast = "(double*)"
-            alpha = f"{cast}dace::blas::BlasConstants::Get().Complex128Pone()"
+            alpha = "dace::blas::BlasConstants::Get().Complex128Pone()"
+            cast = '(double*)'
         else:
             raise ValueError("Unsupported type for OpenBLAS omatcopy extension: " + str(dtype))
         # TODO: Add stride support
@@ -164,8 +178,8 @@ def expansion(node, state, sdfg):
         # Adaptations for BLAS API
         order = 'CblasRowMajor'
         trans = 'CblasTrans'
-        code = ("cblas_{f}({o}, {t}, {m}, {n}, {a}, {c}_inp, "
-                "{n}, {c}_out, {m});").format(f=func, o=order, t=trans, m=m, n=n, a=alpha, c=cast)
+        code = ("cblas_{f}({o}, {t}, {m}, {n}, {cast}{a}, {cast}_inp, "
+                "{n}, {cast}_out, {m});").format(f=func, o=order, t=trans, m=m, n=n, a=alpha, cast=cast)
         tasklet = dace.sdfg.nodes.Tasklet(node.name,
                                           node.in_connectors,
                                           node.out_connectors,
@@ -184,6 +198,11 @@ def expansion(node, state, sdfg, **kwargs):
         node.validate(sdfg, state)
         dtype = node.dtype
 
+        # Fall back to native implementation if input and output types are not the same
+        if (sdfg.arrays[list(state.in_edges_by_connector(node, '_inp'))[0].data.data].dtype != sdfg.arrays[list(
+                state.out_edges_by_connector(node, '_out'))[0].data.data].dtype):
+            return ExpandTransposePure.make_sdfg(node, state, sdfg)
+
         try:
             func, cdtype, factort = blas_helpers.cublas_type_metadata(dtype)
         except TypeError as ex:
diff --git a/tests/library/fft_test.py b/tests/library/fft_test.py
new file mode 100644
index 0000000000..440d0a46cf
--- /dev/null
+++ b/tests/library/fft_test.py
@@ -0,0 +1,101 @@
+# Copyright 2019-2024 ETH Zurich and the DaCe authors. All rights reserved.
+import pytest
+import numpy as np
+
+import dace
+
+
+@pytest.mark.parametrize('symbolic', (False, True))
+def test_fft(symbolic):
+    if symbolic:
+        N = dace.symbol('N')
+    else:
+        N = 21
+
+    @dace.program
+    def tester(x: dace.complex128[N]):
+        return np.fft.fft(x)
+
+    a = np.random.rand(21) + 1j * np.random.rand(21)
+    b = tester(a)
+    assert np.allclose(b, np.fft.fft(a))
+
+
+def test_fft_r2c():
+    """
+    Tests implicit conversion to complex types
+    """
+
+    @dace.program
+    def tester(x: dace.float32[20]):
+        return np.fft.fft(x)
+
+    a = np.random.rand(20).astype(np.float32)
+    b = tester(a)
+    assert b.dtype == np.complex64
+    assert np.allclose(b, np.fft.fft(a))
+
+
+@pytest.mark.parametrize('norm', ('backward', 'forward', 'ortho'))
+def test_ifft(norm):
+
+    @dace.program
+    def tester(x: dace.complex128[21]):
+        return np.fft.ifft(x, norm=norm)
+
+    a = np.random.rand(21) + 1j * np.random.rand(21)
+    b = tester(a)
+    assert np.allclose(b, np.fft.ifft(a, norm=norm))
+
+
+@pytest.mark.gpu
+def test_cufft():
+    import dace.libraries.fft as fftlib
+
+    @dace.program
+    def tester(x: dace.complex128[210]):
+        return np.fft.fft(x)
+
+    sdfg = tester.to_sdfg()
+    sdfg.apply_gpu_transformations()
+    fftlib.FFT.default_implementation = 'cuFFT'
+    sdfg.expand_library_nodes()
+    fftlib.FFT.default_implementation = 'pure'
+
+    a = np.random.rand(210) + 1j * np.random.rand(210)
+    b = sdfg(a)
+    assert np.allclose(b, np.fft.fft(a))
+
+
+@pytest.mark.gpu
+def test_cufft_twoplans():
+    import dace.libraries.fft as fftlib
+
+    @dace.program
+    def tester(x: dace.complex128[210], y: dace.complex64[19]):
+        return np.fft.fft(x), np.fft.ifft(y, norm='forward')
+
+    sdfg = tester.to_sdfg()
+    sdfg.apply_gpu_transformations()
+    fftlib.FFT.default_implementation = 'cuFFT'
+    fftlib.IFFT.default_implementation = 'cuFFT'
+    sdfg.expand_library_nodes()
+    fftlib.FFT.default_implementation = 'pure'
+    fftlib.IFFT.default_implementation = 'pure'
+
+    a = np.random.rand(210) + 1j * np.random.rand(210)
+    b = (np.random.rand(19) + 1j * np.random.rand(19)).astype(np.complex64)
+    c, d = sdfg(a, b)
+    assert np.allclose(c, np.fft.fft(a))
+    assert np.allclose(d, np.fft.ifft(b, norm='forward'))
+
+
+if __name__ == '__main__':
+    test_fft(False)
+    test_fft(True)
+    test_fft_r2c()
+    test_ifft('backward')
+    test_ifft('forward')
+    test_ifft('ortho')
+    test_cufft()
+    test_cufft_twoplans()
diff --git a/tests/numpy/array_creation_test.py b/tests/numpy/array_creation_test.py
index 7329b48b3f..a1f6d0329f 100644
--- a/tests/numpy/array_creation_test.py
+++ b/tests/numpy/array_creation_test.py
@@ -152,6 +152,42 @@ def test_arange_6():
     return np.arange(2.5, 10, 3)
 
 
+@compare_numpy_output()
+def test_linspace_1():
+    return np.linspace(2.5, 10, num=3)
+
+
+@compare_numpy_output()
+def test_linspace_2():
+    space, step = np.linspace(2.5, 10, num=3, retstep=True)
+    return space, step
+
+
+@compare_numpy_output()
+def test_linspace_3():
+    a = np.array([1, 2, 3])
+    return np.linspace(a, 5, num=10)
+
+
+@compare_numpy_output()
+def test_linspace_4():
+    a = np.array([[1, 2, 3], [4, 5, 6]])
+    space, step = np.linspace(a, 10, endpoint=False, retstep=True)
+    return space, step
+
+
+@compare_numpy_output()
+def test_linspace_5():
+    a = np.array([[1, 2, 3], [4, 5, 6]])
+    b = np.array([[5], [10]])
+    return np.linspace(a, b, endpoint=False, axis=1)
+
+
+@compare_numpy_output()
+def test_linspace_6():
+    return np.linspace(-5, 5.5, dtype=np.float32)
+
+
 @dace.program
 def program_strides_0():
     A = dace.ndarray((2, 2), dtype=dace.int32, strides=(2, 1))
@@ -267,6 +303,12 @@ def ones_scalar_size(k: dace.int32):
     test_arange_4()
     test_arange_5()
     test_arange_6()
+    test_linspace_1()
+    test_linspace_2()
+    test_linspace_3()
+    test_linspace_4()
+    test_linspace_5()
+    test_linspace_6()
     test_strides_0()
     test_strides_1()
     test_strides_2()
diff --git a/tests/numpy/attention_simple_test.py b/tests/numpy/attention_simple_test.py
index 49558a154b..2ce0205e3f 100644
--- a/tests/numpy/attention_simple_test.py
+++ b/tests/numpy/attention_simple_test.py
@@ -11,7 +11,7 @@
 def dace_softmax(X_in: dace.float32[N], X_out: dace.float32[N]):
 
     tmp_max = dace.reduce(lambda a, b: max(a, b), X_in)
-    X_out[:] = exp(X_in - tmp_max)
+    X_out[:] = np.exp(X_in - tmp_max)
     tmp_sum = dace.reduce(lambda a, b: a + b, X_out, identity=0)
     X_out[:] /= tmp_sum
 
diff --git a/tests/numpy/attribute_test.py b/tests/numpy/attribute_test.py
index 2181883015..e011eafc89 100644
--- a/tests/numpy/attribute_test.py
+++ b/tests/numpy/attribute_test.py
@@ -54,7 +54,50 @@ def fn(a: dace.float64[N, F_in], b: dace.float64[N, heads, F_out], c: dace.float
     assert np.allclose(c, c_expected)
 
 
+def test_nested_attribute():
+
+    @dace.program
+    def tester(a: dace.complex128[20, 10]):
+        return a.T.real
+
+    r = np.random.rand(20, 10)
+    im = np.random.rand(20, 10)
+    a = r + 1j * im
+    res = tester(a)
+    assert np.allclose(res, r.T)
+
+
+def test_attribute_of_expr():
+    """
+    Regression reported in Issue #1295.
+    """
+
+    @dace.program
+    def tester(a: dace.float64[20, 20], b: dace.float64[20, 20], c: dace.float64[20, 20]):
+        c[:, :] = (a @ b).T
+
+    a = np.random.rand(20, 20)
+    b = np.random.rand(20, 20)
+    c = np.random.rand(20, 20)
+    ref = (a @ b).T
+    tester(a, b, c)
+    assert np.allclose(c, ref)
+
+
+def test_attribute_function():
+
+    @dace.program
+    def tester():
+        return np.arange(10).reshape(10, 1)
+
+    a = tester()
+    assert np.allclose(a, np.arange(10).reshape(10, 1))
+
+
 if __name__ == '__main__':
     test_attribute_in_ranged_loop()
     test_attribute_in_ranged_loop_symbolic()
     test_attribute_new_state()
+    test_nested_attribute()
+    test_attribute_of_expr()
+    test_attribute_function()
diff --git a/tests/numpy/concat_test.py b/tests/numpy/concat_test.py
new file mode 100644
index 0000000000..614258e34f
--- /dev/null
+++ b/tests/numpy/concat_test.py
@@ -0,0 +1,133 @@
+# Copyright 2019-2024 ETH Zurich and the DaCe authors. All rights reserved.
+import dace
+import numpy as np
+from common import compare_numpy_output
+import pytest
+
+M = 10
+N = 20
+K = 30
+
+
+@compare_numpy_output()
+def test_concatenate():
+    a = np.zeros([N, N], dtype=np.float32)
+    b = np.ones([N, 1], dtype=np.float32)
+    return np.concatenate((a, b), axis=-1)
+
+
+@compare_numpy_output()
+def test_concatenate_four():
+    a = np.zeros([N, N], dtype=np.float32)
+    b = np.ones([N, 1], dtype=np.float32)
+    c = np.full([N, M], 2.0, dtype=np.float32)
+    return np.concatenate((a, b, c, a), axis=-1)
+
+
+@compare_numpy_output()
+def test_concatenate_out():
+    a = np.zeros([N, N], dtype=np.float32)
+    b = np.ones([M, N], dtype=np.float32)
+    c = np.full([N + M, N], -1, dtype=np.float32)
+    np.concatenate([a, b], out=c)
+    return c + 1
+
+
+def test_concatenate_symbolic():
+    n = dace.symbol('n')
+    m = dace.symbol('m')
+    k = dace.symbol('k')
+
+    @dace.program
+    def tester(a: dace.float64[k, m], b: dace.float64[k, n]):
+        return np.concatenate((a, b), axis=1)
+
+    aa = np.random.rand(10, 4)
+    bb = np.random.rand(10, 5)
+    cc = tester(aa, bb)
+    assert tuple(cc.shape) == (10, 9)
+    assert np.allclose(np.concatenate((aa, bb), axis=1), cc)
+
+
+def test_concatenate_fail():
+    with pytest.raises(ValueError):
+
+        @dace.program
+        def tester(a: dace.float64[K, M], b: dace.float64[N, K]):
+            return np.concatenate((a, b), axis=1)
+
+        aa = np.random.rand(K, M)
+        bb = np.random.rand(N, K)
+        tester(aa, bb)
+
+
+@compare_numpy_output()
+def test_concatenate_flatten():
+    a = np.zeros([1, 2, 3], dtype=np.float32)
+    b = np.ones([4, 5, 6], dtype=np.float32)
+    return np.concatenate([a, b], axis=None)
+
+
+@compare_numpy_output()
+def test_stack():
+    a = np.zeros([N, M, K], dtype=np.float32)
+    b = np.ones([N, M, K], dtype=np.float32)
+    return np.stack((a, b), axis=-1)
+
+
+@compare_numpy_output()
+def test_vstack():
+    a = np.zeros([N, M], dtype=np.float32)
+    b = np.ones([N, M], dtype=np.float32)
+    return np.vstack((a, b))
+
+
+@compare_numpy_output()
+def test_vstack_1d():
+    a = np.zeros([N], dtype=np.float32)
+    b = np.ones([N], dtype=np.float32)
+    return np.vstack((a, b))
+
+
+@compare_numpy_output()
+def test_hstack():
+    a = np.zeros([N, M], dtype=np.float32)
+    b = np.ones([N, M], dtype=np.float32)
+    return np.hstack((a, b))
+
+
+@compare_numpy_output()
+def test_hstack_1d():
+    a = np.zeros([N], dtype=np.float32)
+    b = np.ones([N], dtype=np.float32)
+    return np.hstack((a, b))
+
+
+@compare_numpy_output()
+def test_dstack():
+    a = np.zeros([N, M, K], dtype=np.float32)
+    b = np.ones([N, M, K], dtype=np.float32)
+    return np.dstack((a, b))
+
+
+@compare_numpy_output()
+def test_dstack_4d():
+    a = np.zeros([N, M, K, K], dtype=np.float32)
+    b = np.ones([N, M, K, K], dtype=np.float32)
+    return np.dstack((a, b))
+
+
+if __name__ == "__main__":
+    test_concatenate()
+    test_concatenate_four()
+    test_concatenate_out()
+    test_concatenate_symbolic()
+    test_concatenate_fail()
+    test_concatenate_flatten()
+    test_stack()
+    test_vstack()
+    test_vstack_1d()
+    test_hstack()
+    test_hstack_1d()
+    test_dstack()
+    test_dstack_4d()
diff --git a/tests/numpy/nested_call_subarray_test.py b/tests/numpy/nested_call_subarray_test.py
index 6a92b004fa..7501652328 100644
--- a/tests/numpy/nested_call_subarray_test.py
+++ b/tests/numpy/nested_call_subarray_test.py
@@ -8,7 +8,7 @@
 @dace.program
 def dace_softmax_ncs(X_in: dace.float32[N], X_out: dace.float32[N]):
     tmp_max = dace.reduce(lambda a, b: a + b, X_in, identity=0)
-    X_out[:] = exp(X_in - tmp_max)
+    X_out[:] = np.exp(X_in - tmp_max)
     tmp_sum = dace.reduce(lambda a, b: max(a, b), X_in)
     X_out[:] /= tmp_sum
 
@@ -22,7 +22,7 @@ def test_ncs_local_program():
     @dace.program
     def dace_softmax_localprog(X_in: dace.float32[N], X_out: dace.float32[N]):
         tmp_max = dace.reduce(lambda a, b: a + b, X_in, identity=0)
-        X_out[:] = exp(X_in - tmp_max)
+        X_out[:] = np.exp(X_in - tmp_max)
         tmp_sum = dace.reduce(lambda a, b: max(a, b), X_in)
         X_out[:] /= tmp_sum
 
diff --git a/tests/numpy/split_test.py b/tests/numpy/split_test.py
new file mode 100644
index 0000000000..e4088754e8
--- /dev/null
+++ b/tests/numpy/split_test.py
@@ -0,0 +1,142 @@
+# Copyright 2019-2024 ETH Zurich and the DaCe authors. All rights reserved.
+"""
+Tests variants of the numpy split array manipulation.
+"""
+import dace
+import numpy as np
+from common import compare_numpy_output
+import pytest
+
+M = 9
+N = 20
+K = 30
+
+
+@compare_numpy_output()
+def test_split():
+    arr = np.arange(M)
+    a, b, c = np.split(arr, 3)
+    return a + b + c
+
+
+def test_uneven_split_fail():
+    with pytest.raises(ValueError):
+
+        @dace.program
+        def tester():
+            arr = np.arange(N)
+            a, b, c = np.split(arr, 3)
+            return a + b + c
+
+        tester()
+
+
+def test_symbolic_split_fail():
+    with pytest.raises(ValueError):
+        n = dace.symbol('n')
+
+        @dace.program
+        def tester():
+            arr = np.arange(N)
+            a, b, c = np.split(arr, n)
+            return a + b + c
+
+        tester()
+
+
+def test_array_split_fail():
+    with pytest.raises(ValueError):
+
+        @dace.program
+        def tester():
+            arr = np.arange(N)
+            split = np.arange(N)
+            a, b, c = np.split(arr, split)
+            return a + b + c
+
+        tester()
+
+
+@compare_numpy_output()
+def test_array_split():
+    arr = np.arange(N)
+    a, b, c = np.array_split(arr, 3)
+    return a, b, c
+
+
+@compare_numpy_output()
+def test_array_split_multidim():
+    arr = np.ones((N, N))
+    a, b, c = np.array_split(arr, 3, axis=1)
+    return a, b, c
+
+
+@compare_numpy_output()
+def test_split_sequence():
+    arr = np.arange(N)
+    a, b = np.split(arr, [3])
+    return a, b
+
+
+@compare_numpy_output()
+def test_split_sequence_2():
+    arr = np.arange(M)
+    a, b, c = np.split(arr, [3, 6])
+    return a + b + c
+
+
+def test_split_sequence_symbolic():
+    n = dace.symbol('n')
+
+    @dace.program
+    def tester(arr: dace.float64[3 * n]):
+        a, b, c = np.split(arr, [n, n + 2])
+        return a, b, c
+
+    nval = K // 3
+    a = np.random.rand(K)
+    ra, rb, rc = tester(a)
+    assert ra.shape[0] == nval
+    assert rb.shape[0] == 2
+    assert rc.shape[0] == K - nval - 2
+    ref = np.split(a, [nval, nval + 2])
+    assert len(ref) == 3
+    assert np.allclose(ra, ref[0])
+    assert np.allclose(rb, ref[1])
+    assert np.allclose(rc, ref[2])
+
+
+@compare_numpy_output()
+def test_vsplit():
+    arr = np.ones((N, M))
+    a, b = np.vsplit(arr, 2)
+    return a, b
+
+
+@compare_numpy_output()
+def test_hsplit():
+    arr = np.ones((M, N))
+    a, b = np.hsplit(arr, 2)
+    return a, b
+
+
+@compare_numpy_output()
+def test_dsplit_4d():
+    arr = np.ones([N, M, K, K], dtype=np.float32)
+    a, b, c = np.dsplit(arr, 3)
+    return a, b, c
+
+
+if __name__ == "__main__":
+    test_split()
+    test_uneven_split_fail()
+    test_symbolic_split_fail()
+    test_array_split_fail()
+    test_array_split()
+    test_array_split_multidim()
+    test_split_sequence()
+    test_split_sequence_2()
+    test_split_sequence_symbolic()
+    test_vsplit()
+    test_hsplit()
+    test_dsplit_4d()
diff --git a/tests/numpy/ufunc_test.py b/tests/numpy/ufunc_test.py
index 06bd4c3189..b769ab1082 100644
--- a/tests/numpy/ufunc_test.py
+++ b/tests/numpy/ufunc_test.py
@@ -1304,6 +1304,11 @@ def test_ufunc_trunc_u(A: dace.uint32[10]):
     return np.trunc(A)
 
 
+@compare_numpy_output()
+def test_ufunc_clip(A: dace.float32[10]):
+    return np.clip(A, 0.2, 0.5)
+
+
 if __name__ == "__main__":
     test_ufunc_add_ff()
     test_ufunc_subtract_ff()
@@ -1542,3 +1547,4 @@ def test_ufunc_trunc_u(A: dace.uint32[10]):
     test_ufunc_trunc_c()
     test_ufunc_trunc_f()
     test_ufunc_trunc_u()
+    test_ufunc_clip()

From 945b5ce4ad26ba9047467d95e75e9aec48792506 Mon Sep 17 00:00:00 2001
From: Philipp Schaad <schaad.phil@gmail.com>
Date: Thu, 31 Oct 2024 12:51:56 +0100
Subject: [PATCH 07/33] Fix jupyter's version of SDFV (#1714)

This requires https://github.com/spcl/dace-webclient/pull/179 to be
merged before being ready.
---
 dace/sdfg/sdfg.py               |   8 +-
 dace/viewer/webclient           |   2 +-
 tutorials/explicit.ipynb        |  35 ++---
 tutorials/getting_started.ipynb | 112 ++++++--------
 tutorials/numpy_frontend.ipynb  |  40 ++---
 tutorials/sdfg_api.ipynb        |  82 ++++++-----
 tutorials/transformations.ipynb | 251 +++++++++++++++-----------------
 7 files changed, 255 insertions(+), 275 deletions(-)

diff --git a/dace/sdfg/sdfg.py b/dace/sdfg/sdfg.py
index f25a6e24d5..cb8a7d5c2d 100644
--- a/dace/sdfg/sdfg.py
+++ b/dace/sdfg/sdfg.py
@@ -1464,9 +1464,11 @@ def _repr_html_(self):
     var sdfg_{uid} = {sdfg};
 </script>
 <script>
-    var sdfv_{uid} = new SDFV();
-    var renderer_{uid} = new SDFGRenderer(sdfv_{uid}, parse_sdfg(sdfg_{uid}),
-        document.getElementById('contents_{uid}'));
+    new SDFGRenderer(
+        checkCompatLoad(parse_sdfg(sdfg_{uid})),
+        document.getElementById("contents_{uid}"),
+        undefined, null, null, false, null, null
+    );
 </script>""".format(
             # Dumping to a string so that Jupyter Javascript can parse it
             # recursively
diff --git a/dace/viewer/webclient b/dace/viewer/webclient
index c6b8fe4fd2..64861bbc05 160000
--- a/dace/viewer/webclient
+++ b/dace/viewer/webclient
@@ -1 +1 @@
-Subproject commit c6b8fe4fd2c3616b0480ead4c24d8012b91a31fd
+Subproject commit 64861bbc054c62bc6cb3f8525bfc4703d6c5e364
diff --git a/tutorials/explicit.ipynb b/tutorials/explicit.ipynb
index 45d172cf35..de718ffc4a 100644
--- a/tutorials/explicit.ipynb
+++ b/tutorials/explicit.ipynb
@@ -123,15 +123,17 @@
       "text/html": [
        "\n",
        "<div class=\"sdfv\">\n",
-       "<div id=\"contents_5749918072939441446\" style=\"position: relative; resize: vertical; overflow: auto\"></div>\n",
+       "<div id=\"contents_1157980253020128038\" style=\"position: relative; resize: vertical; overflow: auto\"></div>\n",
        "</div>\n",
        "<script>\n",
-       "    var sdfg_5749918072939441446 = \"{\\n  \\\"type\\\": \\\"SDFG\\\",\\n  \\\"attributes\\\": {\\n    \\\"name\\\": \\\"transpose\\\",\\n    \\\"arg_names\\\": [\\n      \\\"A\\\",\\n      \\\"B\\\"\\n    ],\\n    \\\"constants_prop\\\": {},\\n    \\\"_arrays\\\": {\\n      \\\"A\\\": {\\n        \\\"type\\\": \\\"Array\\\",\\n        \\\"attributes\\\": {\\n          \\\"allow_conflicts\\\": false,\\n          \\\"strides\\\": [\\n            \\\"N\\\",\\n            \\\"1\\\"\\n          ],\\n          \\\"total_size\\\": \\\"M*N\\\",\\n          \\\"offset\\\": [\\n            \\\"0\\\",\\n            \\\"0\\\"\\n          ],\\n          \\\"may_alias\\\": false,\\n          \\\"alignment\\\": 0,\\n          \\\"start_offset\\\": 0,\\n          \\\"optional\\\": false,\\n          \\\"pool\\\": false,\\n          \\\"dtype\\\": \\\"float32\\\",\\n          \\\"shape\\\": [\\n            \\\"M\\\",\\n            \\\"N\\\"\\n          ],\\n          \\\"transient\\\": false,\\n          \\\"storage\\\": \\\"Default\\\",\\n          \\\"lifetime\\\": \\\"Scope\\\",\\n          \\\"location\\\": {},\\n          \\\"debuginfo\\\": null\\n        }\\n      },\\n      \\\"B\\\": {\\n        \\\"type\\\": \\\"Array\\\",\\n        \\\"attributes\\\": {\\n          \\\"allow_conflicts\\\": false,\\n          \\\"strides\\\": [\\n            \\\"M\\\",\\n            \\\"1\\\"\\n          ],\\n          \\\"total_size\\\": \\\"M*N\\\",\\n          \\\"offset\\\": [\\n            \\\"0\\\",\\n            \\\"0\\\"\\n          ],\\n          \\\"may_alias\\\": false,\\n          \\\"alignment\\\": 0,\\n          \\\"start_offset\\\": 0,\\n          \\\"optional\\\": false,\\n          \\\"pool\\\": false,\\n          \\\"dtype\\\": \\\"float32\\\",\\n          \\\"shape\\\": [\\n            \\\"N\\\",\\n            \\\"M\\\"\\n          ],\\n          \\\"transient\\\": false,\\n          \\\"storage\\\": \\\"Default\\\",\\n          \\\"lifetime\\\": \\\"Scope\\\",\\n          \\\"location\\\": {},\\n          \\\"debuginfo\\\": null\\n        }\\n      }\\n    },\\n    \\\"symbols\\\": {\\n      \\\"M\\\": \\\"int32\\\",\\n      \\\"N\\\": \\\"int32\\\"\\n    },\\n    \\\"instrument\\\": \\\"No_Instrumentation\\\",\\n    \\\"global_code\\\": {\\n      \\\"frame\\\": {\\n        \\\"string_data\\\": \\\"\\\",\\n        \\\"language\\\": \\\"CPP\\\"\\n      }\\n    },\\n    \\\"init_code\\\": {\\n      \\\"frame\\\": {\\n        \\\"string_data\\\": \\\"\\\",\\n        \\\"language\\\": \\\"CPP\\\"\\n      }\\n    },\\n    \\\"exit_code\\\": {\\n      \\\"frame\\\": {\\n        \\\"string_data\\\": \\\"\\\",\\n        \\\"language\\\": \\\"CPP\\\"\\n      }\\n    },\\n    \\\"orig_sdfg\\\": null,\\n    \\\"transformation_hist\\\": [],\\n    \\\"logical_groups\\\": [],\\n    \\\"openmp_sections\\\": false,\\n    \\\"debuginfo\\\": {\\n      \\\"type\\\": \\\"DebugInfo\\\",\\n      \\\"start_line\\\": 1,\\n      \\\"end_line\\\": 13,\\n      \\\"start_column\\\": 0,\\n      \\\"end_column\\\": 0,\\n      \\\"filename\\\": \\\"/tmp/ipykernel_29737/1388926337.py\\\"\\n    },\\n    \\\"_pgrids\\\": {},\\n    \\\"_subarrays\\\": {},\\n    \\\"_rdistrarrays\\\": {},\\n    \\\"callback_mapping\\\": {},\\n    \\\"is_collapsed\\\": false\\n  },\\n  \\\"nodes\\\": [\\n    {\\n      \\\"type\\\": \\\"SDFGState\\\",\\n      \\\"label\\\": \\\"s6_4\\\",\\n      \\\"id\\\": 0,\\n      \\\"collapsed\\\": false,\\n      \\\"scope_dict\\\": {\\n        \\\"-1\\\": [\\n          0,\\n          2,\\n          3\\n        ],\\n        \\\"0\\\": [\\n          1,\\n          4\\n        ]\\n      },\\n      \\\"nodes\\\": [\\n        {\\n          \\\"type\\\": \\\"MapEntry\\\",\\n          \\\"label\\\": \\\"mytasklet[i=0:M, j=0:N]\\\",\\n          \\\"attributes\\\": {\\n            \\\"label\\\": \\\"mytasklet\\\",\\n            \\\"params\\\": [\\n              \\\"i\\\",\\n              \\\"j\\\"\\n            ],\\n            \\\"range\\\": {\\n              \\\"type\\\": \\\"Range\\\",\\n              \\\"ranges\\\": [\\n                {\\n                  \\\"start\\\": \\\"0\\\",\\n                  \\\"end\\\": \\\"M - 1\\\",\\n                  \\\"step\\\": \\\"1\\\",\\n                  \\\"tile\\\": \\\"1\\\"\\n                },\\n                {\\n                  \\\"start\\\": \\\"0\\\",\\n                  \\\"end\\\": \\\"N - 1\\\",\\n                  \\\"step\\\": \\\"1\\\",\\n                  \\\"tile\\\": \\\"1\\\"\\n                }\\n              ]\\n            },\\n            \\\"schedule\\\": \\\"Default\\\",\\n            \\\"unroll\\\": false,\\n            \\\"collapse\\\": 1,\\n            \\\"debuginfo\\\": {\\n              \\\"type\\\": \\\"DebugInfo\\\",\\n              \\\"start_line\\\": 6,\\n              \\\"end_line\\\": 6,\\n              \\\"start_column\\\": 4,\\n              \\\"end_column\\\": 4,\\n              \\\"filename\\\": 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        "</script>\n",
        "<script>\n",
-       "    var sdfv_5749918072939441446 = new SDFV();\n",
-       "    var renderer_5749918072939441446 = new SDFGRenderer(sdfv_5749918072939441446, parse_sdfg(sdfg_5749918072939441446),\n",
-       "        document.getElementById('contents_5749918072939441446'));\n",
+       "    new SDFGRenderer(\n",
+       "        checkCompatLoad(parse_sdfg(sdfg_1157980253020128038)),\n",
+       "        document.getElementById(\"contents_1157980253020128038\"),\n",
+       "        undefined, null, null, false, null, null\n",
+       "    );\n",
        "</script>"
       ],
       "text/plain": [
@@ -159,16 +161,7 @@
    "cell_type": "code",
    "execution_count": 6,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "WARNING: Casting scalar argument \"M\" from int to <class 'numpy.int32'>\n",
-      "WARNING: Casting scalar argument \"N\" from int to <class 'numpy.int32'>\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "sdfg(A=A, B=B, M=A.shape[0], N=A.shape[1])"
    ]
@@ -201,7 +194,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -225,7 +218,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -310,13 +303,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "WARNING: Casting scalar argument \"threshold\" from int to <class 'numpy.int32'>\n"
+      "WARNING: Passing uint32 array argument \"outsz\" to a int32 array\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "array([121], dtype=uint32)"
+       "array([114], dtype=uint32)"
       ]
      },
      "execution_count": 13,
@@ -351,7 +344,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "dace_dev",
    "language": "python",
    "name": "python3"
   },
@@ -365,7 +358,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.1"
+   "version": "3.12.0"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/getting_started.ipynb b/tutorials/getting_started.ipynb
index 4405c28d56..266d207abc 100644
--- a/tutorials/getting_started.ipynb
+++ b/tutorials/getting_started.ipynb
@@ -13,22 +13,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 16,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<script src=\"https://spcl.github.io/dace-webclient/dist/sdfv.js\"></script>\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "import dace"
    ]
@@ -42,7 +29,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -66,8 +53,8 @@
     {
      "data": {
       "text/plain": [
-       "array([[0.74867876, 0.85403223, 0.16573784],\n",
-       "       [0.71994615, 0.29855314, 0.21483992]])"
+       "array([[0.02638476, 0.15801766, 0.60640768],\n",
+       "       [0.75281897, 0.02027034, 0.92066681]])"
       ]
      },
      "execution_count": 3,
@@ -89,8 +76,8 @@
     {
      "data": {
       "text/plain": [
-       "array([[1.49735752, 1.70806445, 0.33147568],\n",
-       "       [1.4398923 , 0.59710627, 0.42967985]])"
+       "array([[0.05276951, 0.31603533, 1.21281536],\n",
+       "       [1.50563794, 0.04054068, 1.84133362]])"
       ]
      },
      "execution_count": 4,
@@ -113,7 +100,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
@@ -121,22 +108,21 @@
       "text/html": [
        "\n",
        "<div class=\"sdfv\">\n",
-       "<div id=\"contents_7583481425765355686\" style=\"position: relative; resize: vertical; overflow: auto\"></div>\n",
+       "<div id=\"contents_7509160133276110954\" style=\"position: relative; resize: vertical; overflow: auto\"></div>\n",
        "</div>\n",
        "<script>\n",
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        "</script>\n",
        "<script>\n",
-       "    var sdfv_7583481425765355686 = new SDFV();\n",
-       "    var renderer_7583481425765355686 = new SDFGRenderer(sdfv_7583481425765355686, parse_sdfg(sdfg_7583481425765355686),\n",
-       "        document.getElementById('contents_7583481425765355686'));\n",
+       "    WebSDFV.getInstance().init();\n",
+       "    WebSDFV.getInstance().setSDFG(checkCompatLoad(parse_sdfg(sdfg_7509160133276110954)), null, false, \"contents_7509160133276110954\");\n",
        "</script>"
       ],
       "text/plain": [
        "SDFG (getstarted)"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -174,7 +160,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -190,7 +176,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -201,7 +187,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
@@ -209,22 +195,21 @@
       "text/html": [
        "\n",
        "<div class=\"sdfv\">\n",
-       "<div id=\"contents_819653159071402806\" style=\"position: relative; resize: vertical; overflow: auto\"></div>\n",
+       "<div id=\"contents_7131181372205319896\" style=\"position: relative; resize: vertical; overflow: auto\"></div>\n",
        "</div>\n",
        "<script>\n",
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        "</script>\n",
        "<script>\n",
-       "    var sdfv_819653159071402806 = new SDFV();\n",
-       "    var renderer_819653159071402806 = new SDFGRenderer(sdfv_819653159071402806, parse_sdfg(sdfg_819653159071402806),\n",
-       "        document.getElementById('contents_819653159071402806'));\n",
+       "    WebSDFV.getInstance().init();\n",
+       "    WebSDFV.getInstance().setSDFG(checkCompatLoad(parse_sdfg(sdfg_7131181372205319896)), null, false, \"contents_7131181372205319896\");\n",
        "</script>"
       ],
       "text/plain": [
        "SDFG (getstarted_sym)"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -248,19 +233,19 @@
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-       "array([[1.63216549, 1.26522381, 0.21606686, ..., 0.56988572, 1.12572538,\n",
-       "        1.72701877],\n",
-       "       [0.3829452 , 1.52386969, 0.82165197, ..., 1.3105662 , 1.19336786,\n",
-       "        1.43671993],\n",
-       "       [1.55277426, 1.50918516, 1.30665626, ..., 1.06562809, 1.53069088,\n",
-       "        1.10071159],\n",
+       "array([[0.98818461, 1.27933885, 0.2033508 , ..., 0.547033  , 0.4299565 ,\n",
+       "        0.24654365],\n",
+       "       [1.91945996, 0.8587834 , 1.6074685 , ..., 0.60969216, 1.7881462 ,\n",
+       "        1.6251679 ],\n",
+       "       [0.09656663, 0.86573612, 0.79912191, ..., 1.50199177, 0.14342504,\n",
+       "        0.77152323],\n",
        "       ...,\n",
-       "       [0.60629736, 1.73240929, 1.26797782, ..., 1.72034476, 1.56691557,\n",
-       "        0.22283613],\n",
-       "       [1.96245486, 1.60559508, 0.02009914, ..., 1.40944583, 1.44560312,\n",
-       "        0.37804927],\n",
-       "       [1.17875002, 0.96963921, 0.28278902, ..., 1.56747976, 0.4616313 ,\n",
-       "        0.94999278]])"
+       "       [1.86926975, 0.16524055, 0.57659078, ..., 0.06706506, 1.94858343,\n",
+       "        0.21332081],\n",
+       "       [0.78987173, 0.32493361, 0.33111051, ..., 0.41438505, 1.6625166 ,\n",
+       "        1.4539469 ],\n",
+       "       [0.32619914, 0.84155838, 0.85757214, ..., 0.93809   , 0.25236549,\n",
+       "        1.95588663]])"
       ]
      },
      "execution_count": 9,
@@ -283,7 +268,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -299,7 +284,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -315,7 +300,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -324,14 +309,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "12 ms ± 143 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
+      "12 ms ± 258 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
      ]
     }
    ],
@@ -341,14 +326,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "3.86 ms ± 271 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
+      "5.1 ms ± 470 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
      ]
     }
    ],
@@ -367,7 +352,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [
     {
@@ -375,22 +360,21 @@
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+       "<div id=\"contents_8965799983179316592\" style=\"position: relative; resize: vertical; overflow: auto\"></div>\n",
        "</div>\n",
        "<script>\n",
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        "<script>\n",
-       "    var sdfv_2432391530722162566 = new SDFV();\n",
-       "    var renderer_2432391530722162566 = new SDFGRenderer(sdfv_2432391530722162566, parse_sdfg(sdfg_2432391530722162566),\n",
-       "        document.getElementById('contents_2432391530722162566'));\n",
+       "    WebSDFV.getInstance().init();\n",
+       "    WebSDFV.getInstance().setSDFG(checkCompatLoad(parse_sdfg(sdfg_8965799983179316592)), null, false, \"contents_8965799983179316592\");\n",
        "</script>"
       ],
       "text/plain": [
        "SDFG (sse_sigma)"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 22,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -422,7 +406,7 @@
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-   "display_name": "Python 3",
+   "display_name": "dace_dev",
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@@ -436,7 +420,7 @@
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    "nbconvert_exporter": "python",
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+   "version": "3.12.0"
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diff --git a/tutorials/numpy_frontend.ipynb b/tutorials/numpy_frontend.ipynb
index fafda2f1b1..83ca6875ba 100644
--- a/tutorials/numpy_frontend.ipynb
+++ b/tutorials/numpy_frontend.ipynb
@@ -107,15 +107,17 @@
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        "<script>\n",
-       "    var sdfv_368274630370787412 = new SDFV();\n",
-       "    var renderer_368274630370787412 = new SDFGRenderer(sdfv_368274630370787412, parse_sdfg(sdfg_368274630370787412),\n",
-       "        document.getElementById('contents_368274630370787412'));\n",
+       "    new SDFGRenderer(\n",
+       "        checkCompatLoad(parse_sdfg(sdfg_5830481020335575841)),\n",
+       "        document.getElementById(\"contents_5830481020335575841\"),\n",
+       "        undefined, null, null, false, null, null\n",
+       "    );\n",
        "</script>"
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        "</script>\n",
        "<script>\n",
-       "    var sdfv_7929264604669305318 = new SDFV();\n",
-       "    var renderer_7929264604669305318 = new SDFGRenderer(sdfv_7929264604669305318, parse_sdfg(sdfg_7929264604669305318),\n",
-       "        document.getElementById('contents_7929264604669305318'));\n",
+       "    new SDFGRenderer(\n",
+       "        checkCompatLoad(parse_sdfg(sdfg_579011172882362224)),\n",
+       "        document.getElementById(\"contents_579011172882362224\"),\n",
+       "        undefined, null, null, false, null, null\n",
+       "    );\n",
        "</script>"
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        "</script>\n",
        "<script>\n",
-       "    var sdfv_8170507351418367833 = new SDFV();\n",
-       "    var renderer_8170507351418367833 = new SDFGRenderer(sdfv_8170507351418367833, parse_sdfg(sdfg_8170507351418367833),\n",
-       "        document.getElementById('contents_8170507351418367833'));\n",
+       "    new SDFGRenderer(\n",
+       "        checkCompatLoad(parse_sdfg(sdfg_6694674476793656679)),\n",
+       "        document.getElementById(\"contents_6694674476793656679\"),\n",
+       "        undefined, null, null, false, null, null\n",
+       "    );\n",
        "</script>"
       ],
       "text/plain": [
@@ -461,7 +467,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "dace_dev",
    "language": "python",
    "name": "python3"
   },
@@ -475,7 +481,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.1"
+   "version": "3.12.0"
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  "nbformat": 4,
diff --git a/tutorials/sdfg_api.ipynb b/tutorials/sdfg_api.ipynb
index 645158ce88..beb4f4b6b0 100644
--- a/tutorials/sdfg_api.ipynb
+++ b/tutorials/sdfg_api.ipynb
@@ -112,15 +112,17 @@
       "text/html": [
        "\n",
        "<div class=\"sdfv\">\n",
-       "<div id=\"contents_3674436108012332988\" style=\"position: relative; resize: vertical; overflow: auto\"></div>\n",
+       "<div id=\"contents_911039905222246626\" style=\"position: relative; resize: vertical; overflow: auto\"></div>\n",
        "</div>\n",
        "<script>\n",
-       "    var sdfg_3674436108012332988 = \"{\\n  \\\"type\\\": \\\"SDFG\\\",\\n  \\\"attributes\\\": {\\n    \\\"name\\\": \\\"jacobi2d\\\",\\n    \\\"arg_names\\\": [],\\n    \\\"constants_prop\\\": {},\\n    \\\"_arrays\\\": {\\n      \\\"A\\\": {\\n        \\\"type\\\": \\\"Array\\\",\\n        \\\"attributes\\\": {\\n          \\\"allow_conflicts\\\": false,\\n          \\\"strides\\\": [\\n            \\\"N\\\",\\n            \\\"1\\\"\\n          ],\\n          \\\"total_size\\\": \\\"N**2\\\",\\n          \\\"offset\\\": [\\n            \\\"0\\\",\\n            \\\"0\\\"\\n          ],\\n          \\\"may_alias\\\": false,\\n          \\\"alignment\\\": 0,\\n          \\\"start_offset\\\": 0,\\n          \\\"optional\\\": null,\\n          \\\"pool\\\": false,\\n          \\\"dtype\\\": \\\"float32\\\",\\n          \\\"shape\\\": [\\n            \\\"N\\\",\\n            \\\"N\\\"\\n          ],\\n          \\\"transient\\\": false,\\n          \\\"storage\\\": \\\"Default\\\",\\n          \\\"lifetime\\\": \\\"Scope\\\",\\n          \\\"location\\\": {},\\n          \\\"debuginfo\\\": null\\n        }\\n      },\\n      \\\"tmp\\\": {\\n        \\\"type\\\": \\\"Array\\\",\\n        \\\"attributes\\\": {\\n          \\\"allow_conflicts\\\": false,\\n          \\\"strides\\\": [\\n            \\\"N\\\",\\n            \\\"1\\\"\\n          ],\\n          \\\"total_size\\\": \\\"N**2\\\",\\n          \\\"offset\\\": [\\n            \\\"0\\\",\\n            \\\"0\\\"\\n          ],\\n          \\\"may_alias\\\": false,\\n          \\\"alignment\\\": 0,\\n          \\\"start_offset\\\": 0,\\n          \\\"optional\\\": false,\\n          \\\"pool\\\": false,\\n          \\\"dtype\\\": \\\"float32\\\",\\n          \\\"shape\\\": [\\n            \\\"N\\\",\\n            \\\"N\\\"\\n          ],\\n          \\\"transient\\\": true,\\n          \\\"storage\\\": \\\"Default\\\",\\n          \\\"lifetime\\\": \\\"Scope\\\",\\n          \\\"location\\\": {},\\n          \\\"debuginfo\\\": null\\n        }\\n      }\\n    },\\n    \\\"symbols\\\": {\\n      \\\"N\\\": \\\"int32\\\"\\n    },\\n    \\\"instrument\\\": \\\"No_Instrumentation\\\",\\n    \\\"global_code\\\": {\\n      \\\"frame\\\": {\\n        \\\"string_data\\\": \\\"\\\",\\n        \\\"language\\\": \\\"CPP\\\"\\n      }\\n    },\\n    \\\"init_code\\\": {\\n      \\\"frame\\\": {\\n        \\\"string_data\\\": \\\"\\\",\\n        \\\"language\\\": \\\"CPP\\\"\\n      }\\n    },\\n    \\\"exit_code\\\": {\\n      \\\"frame\\\": {\\n        \\\"string_data\\\": \\\"\\\",\\n        \\\"language\\\": \\\"CPP\\\"\\n      }\\n    },\\n    \\\"orig_sdfg\\\": null,\\n    \\\"transformation_hist\\\": [],\\n    \\\"logical_groups\\\": [],\\n    \\\"openmp_sections\\\": false,\\n    \\\"debuginfo\\\": {\\n      \\\"type\\\": \\\"DebugInfo\\\",\\n      \\\"start_line\\\": 0,\\n      \\\"end_line\\\": 0,\\n      \\\"start_column\\\": 0,\\n      \\\"end_column\\\": 0,\\n      \\\"filename\\\": null\\n    },\\n    \\\"_pgrids\\\": {},\\n    \\\"_subarrays\\\": {},\\n    \\\"_rdistrarrays\\\": {},\\n    \\\"callback_mapping\\\": {},\\n    \\\"is_collapsed\\\": false\\n  },\\n  \\\"nodes\\\": [\\n    {\\n      \\\"type\\\": \\\"SDFGState\\\",\\n      \\\"label\\\": \\\"state\\\",\\n      \\\"id\\\": 0,\\n      \\\"collapsed\\\": false,\\n      \\\"scope_dict\\\": {\\n        \\\"-1\\\": []\\n      },\\n      \\\"nodes\\\": [],\\n      \\\"edges\\\": [],\\n      \\\"attributes\\\": {\\n        \\\"nosync\\\": false,\\n        \\\"instrument\\\": \\\"No_Instrumentation\\\",\\n        \\\"symbol_instrument\\\": \\\"No_Instrumentation\\\",\\n        \\\"symbol_instrument_condition\\\": {\\n          \\\"string_data\\\": \\\"1\\\",\\n          \\\"language\\\": \\\"CPP\\\"\\n        },\\n        \\\"executions\\\": \\\"0\\\",\\n        \\\"dynamic_executions\\\": true,\\n        \\\"ranges\\\": {},\\n        \\\"location\\\": {},\\n        \\\"is_collapsed\\\": false\\n      }\\n    }\\n  ],\\n  \\\"edges\\\": [],\\n  \\\"collapsed\\\": false,\\n  \\\"label\\\": \\\"\\\",\\n  \\\"id\\\": null,\\n  \\\"sdfg_list_id\\\": 0,\\n  \\\"start_state\\\": null,\\n  \\\"dace_version\\\": \\\"0.15.1\\\"\\n}\";\n",
+       "    var sdfg_911039905222246626 = \"{\\n  \\\"type\\\": \\\"SDFG\\\",\\n  \\\"attributes\\\": {\\n    \\\"name\\\": \\\"jacobi2d\\\",\\n    \\\"_arrays\\\": {\\n      \\\"A\\\": {\\n        \\\"type\\\": \\\"Array\\\",\\n        \\\"attributes\\\": {\\n          \\\"strides\\\": [\\n            \\\"N\\\",\\n            \\\"1\\\"\\n          ],\\n          \\\"total_size\\\": \\\"N**2\\\",\\n          \\\"offset\\\": [\\n            \\\"0\\\",\\n            \\\"0\\\"\\n          ],\\n          \\\"dtype\\\": \\\"float32\\\",\\n          \\\"shape\\\": [\\n            \\\"N\\\",\\n            \\\"N\\\"\\n          ],\\n          \\\"debuginfo\\\": null\\n        }\\n      },\\n      \\\"tmp\\\": {\\n        \\\"type\\\": \\\"Array\\\",\\n        \\\"attributes\\\": {\\n          \\\"strides\\\": [\\n            \\\"N\\\",\\n            \\\"1\\\"\\n          ],\\n          \\\"total_size\\\": \\\"N**2\\\",\\n          \\\"offset\\\": [\\n            \\\"0\\\",\\n            \\\"0\\\"\\n          ],\\n          \\\"optional\\\": false,\\n          \\\"dtype\\\": \\\"float32\\\",\\n          \\\"shape\\\": [\\n            \\\"N\\\",\\n            \\\"N\\\"\\n          ],\\n          \\\"transient\\\": true,\\n          \\\"debuginfo\\\": null\\n        }\\n      }\\n    },\\n    \\\"symbols\\\": {\\n      \\\"N\\\": \\\"int32\\\"\\n    },\\n    \\\"global_code\\\": {\\n      \\\"frame\\\": {\\n        \\\"string_data\\\": \\\"\\\",\\n        \\\"language\\\": \\\"CPP\\\"\\n      }\\n    },\\n    \\\"init_code\\\": {\\n      \\\"frame\\\": {\\n        \\\"string_data\\\": \\\"\\\",\\n        \\\"language\\\": \\\"CPP\\\"\\n      }\\n    },\\n    \\\"exit_code\\\": {\\n      \\\"frame\\\": {\\n        \\\"string_data\\\": \\\"\\\",\\n        \\\"language\\\": \\\"CPP\\\"\\n      }\\n    },\\n    \\\"guid\\\": \\\"e089ba98-1237-4d2c-afc9-50a6d63ec569\\\"\\n  },\\n  \\\"nodes\\\": [\\n    {\\n      \\\"type\\\": \\\"SDFGState\\\",\\n      \\\"label\\\": \\\"block\\\",\\n      \\\"id\\\": 0,\\n      \\\"collapsed\\\": false,\\n      \\\"scope_dict\\\": {\\n        \\\"-1\\\": []\\n      },\\n      \\\"nodes\\\": [],\\n      \\\"edges\\\": [],\\n      \\\"attributes\\\": {\\n        \\\"guid\\\": \\\"08787487-27df-47ed-a055-83f1a15cc610\\\"\\n      }\\n    }\\n  ],\\n  \\\"edges\\\": [],\\n  \\\"collapsed\\\": false,\\n  \\\"label\\\": \\\"\\\",\\n  \\\"id\\\": null,\\n  \\\"cfg_list_id\\\": 0,\\n  \\\"start_block\\\": null,\\n  \\\"dace_version\\\": \\\"0.16.1\\\"\\n}\";\n",
        "</script>\n",
        "<script>\n",
-       "    var sdfv_3674436108012332988 = new SDFV();\n",
-       "    var renderer_3674436108012332988 = new SDFGRenderer(sdfv_3674436108012332988, parse_sdfg(sdfg_3674436108012332988),\n",
-       "        document.getElementById('contents_3674436108012332988'));\n",
+       "    new SDFGRenderer(\n",
+       "        checkCompatLoad(parse_sdfg(sdfg_911039905222246626)),\n",
+       "        document.getElementById(\"contents_911039905222246626\"),\n",
+       "        undefined, null, null, false, null, null\n",
+       "    );\n",
        "</script>"
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@@ -200,15 +202,17 @@
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        "\n",
        "<div class=\"sdfv\">\n",
-       "<div id=\"contents_8138999558471292852\" style=\"position: relative; resize: vertical; overflow: auto\"></div>\n",
+       "<div id=\"contents_1432515683626435250\" style=\"position: relative; resize: vertical; overflow: auto\"></div>\n",
        "</div>\n",
        "<script>\n",
-       "    var sdfg_8138999558471292852 = \"{\\n  \\\"type\\\": \\\"SDFG\\\",\\n  \\\"attributes\\\": {\\n    \\\"name\\\": \\\"jacobi2d\\\",\\n    \\\"arg_names\\\": [],\\n    \\\"constants_prop\\\": {},\\n    \\\"_arrays\\\": {\\n      \\\"A\\\": {\\n        \\\"type\\\": \\\"Array\\\",\\n        \\\"attributes\\\": {\\n          \\\"allow_conflicts\\\": false,\\n          \\\"strides\\\": [\\n            \\\"N\\\",\\n            \\\"1\\\"\\n          ],\\n          \\\"total_size\\\": \\\"N**2\\\",\\n          \\\"offset\\\": [\\n            \\\"0\\\",\\n            \\\"0\\\"\\n          ],\\n          \\\"may_alias\\\": false,\\n          \\\"alignment\\\": 0,\\n          \\\"start_offset\\\": 0,\\n          \\\"optional\\\": null,\\n          \\\"pool\\\": false,\\n          \\\"dtype\\\": \\\"float32\\\",\\n          \\\"shape\\\": [\\n            \\\"N\\\",\\n            \\\"N\\\"\\n          ],\\n          \\\"transient\\\": false,\\n          \\\"storage\\\": 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        "<script>\n",
-       "    var sdfv_8138999558471292852 = new SDFV();\n",
-       "    var renderer_8138999558471292852 = new SDFGRenderer(sdfv_8138999558471292852, parse_sdfg(sdfg_8138999558471292852),\n",
-       "        document.getElementById('contents_8138999558471292852'));\n",
+       "    new SDFGRenderer(\n",
+       "        checkCompatLoad(parse_sdfg(sdfg_1432515683626435250)),\n",
+       "        document.getElementById(\"contents_1432515683626435250\"),\n",
+       "        undefined, null, null, false, null, null\n",
+       "    );\n",
        "</script>"
       ],
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@@ -240,15 +244,17 @@
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-       "    var sdfv_1436658196592004014 = new SDFV();\n",
-       "    var renderer_1436658196592004014 = new SDFGRenderer(sdfv_1436658196592004014, parse_sdfg(sdfg_1436658196592004014),\n",
-       "        document.getElementById('contents_1436658196592004014'));\n",
+       "    new SDFGRenderer(\n",
+       "        checkCompatLoad(parse_sdfg(sdfg_1721424513678918943)),\n",
+       "        document.getElementById(\"contents_1721424513678918943\"),\n",
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        "</script>\n",
        "<script>\n",
-       "    var sdfv_231614054952564473 = new SDFV();\n",
-       "    var renderer_231614054952564473 = new SDFGRenderer(sdfv_231614054952564473, parse_sdfg(sdfg_231614054952564473),\n",
-       "        document.getElementById('contents_231614054952564473'));\n",
+       "    new SDFGRenderer(\n",
+       "        checkCompatLoad(parse_sdfg(sdfg_2757813617883732974)),\n",
+       "        document.getElementById(\"contents_2757813617883732974\"),\n",
+       "        undefined, null, null, false, null, null\n",
+       "    );\n",
        "</script>"
       ],
       "text/plain": [
@@ -477,7 +489,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -486,14 +498,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Difference: 1.6358224e-06\n"
+      "Difference: 7.1136246\n"
      ]
     }
    ],
@@ -504,7 +516,7 @@
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   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "dace_dev",
    "language": "python",
    "name": "python3"
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@@ -518,7 +530,7 @@
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    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.1"
+   "version": "3.12.0"
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diff --git a/tutorials/transformations.ipynb b/tutorials/transformations.ipynb
index d54b294e6e..931df79e18 100644
--- a/tutorials/transformations.ipynb
+++ b/tutorials/transformations.ipynb
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        "<script>\n",
-       "    var sdfv_2092156200105880731 = new SDFV();\n",
-       "    var renderer_2092156200105880731 = new SDFGRenderer(sdfv_2092156200105880731, parse_sdfg(sdfg_2092156200105880731),\n",
-       "        document.getElementById('contents_2092156200105880731'));\n",
+       "    new SDFGRenderer(\n",
+       "        checkCompatLoad(parse_sdfg(sdfg_1456974827647142959)),\n",
+       "        document.getElementById(\"contents_1456974827647142959\"),\n",
+       "        undefined, null, null, false, null, null\n",
+       "    );\n",
        "</script>"
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\\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    }\\n                  ]\\n                },\\n                \\\"is_data_src\\\": false,\\n                \\\"num_accesses\\\": \\\"1000000\\\"\\n              }\\n            }\\n          },\\n          \\\"src\\\": \\\"7\\\",\\n          \\\"dst\\\": \\\"5\\\",\\n          \\\"dst_connector\\\": null,\\n          \\\"src_connector\\\": \\\"OUT_1\\\"\\n        },\\n        {\\n          \\\"type\\\": \\\"MultiConnectorEdge\\\",\\n          \\\"attributes\\\": {\\n            \\\"data\\\": {\\n              \\\"type\\\": \\\"Memlet\\\",\\n              \\\"attributes\\\": {\\n                \\\"volume\\\": \\\"1\\\",\\n                \\\"subset\\\": {\\n                  \\\"type\\\": \\\"Range\\\",\\n                  \\\"ranges\\\": [\\n                    {\\n                      \\\"start\\\": \\\"__i0\\\",\\n                      \\\"end\\\": \\\"__i0\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    },\\n                    {\\n                      \\\"start\\\": \\\"__i1\\\",\\n                      \\\"end\\\": \\\"__i1\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    }\\n                  ]\\n                },\\n                \\\"data\\\": \\\"B\\\",\\n                \\\"debuginfo\\\": null,\\n                \\\"guid\\\": \\\"2b0e9c37-6c9f-4208-9236-f51a0d80c63b\\\",\\n                \\\"src_subset\\\": {\\n                  \\\"type\\\": \\\"Range\\\",\\n                  \\\"ranges\\\": [\\n                    {\\n                      \\\"start\\\": \\\"__i0\\\",\\n                      \\\"end\\\": \\\"__i0\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    },\\n                    {\\n                      \\\"start\\\": \\\"__i1\\\",\\n                      \\\"end\\\": \\\"__i1\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    }\\n                  ]\\n                },\\n                \\\"dst_subset\\\": null,\\n                \\\"is_data_src\\\": true,\\n                \\\"num_accesses\\\": \\\"1\\\"\\n              }\\n            }\\n          },\\n          \\\"src\\\": \\\"6\\\",\\n          \\\"dst\\\": \\\"0\\\",\\n          \\\"dst_connector\\\": \\\"__in1\\\",\\n          \\\"src_connector\\\": \\\"OUT_1\\\"\\n        },\\n        {\\n          \\\"type\\\": \\\"MultiConnectorEdge\\\",\\n          \\\"attributes\\\": {\\n            \\\"data\\\": {\\n              \\\"type\\\": \\\"Memlet\\\",\\n              \\\"attributes\\\": {\\n                \\\"volume\\\": \\\"1\\\",\\n                \\\"subset\\\": {\\n                  \\\"type\\\": \\\"Range\\\",\\n                  \\\"ranges\\\": [\\n                    {\\n                      \\\"start\\\": \\\"__i0\\\",\\n                      \\\"end\\\": \\\"__i0\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    },\\n                    {\\n                      \\\"start\\\": \\\"__i1\\\",\\n                      \\\"end\\\": \\\"__i1\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    }\\n                  ]\\n                },\\n                \\\"data\\\": \\\"B\\\",\\n                \\\"debuginfo\\\": null,\\n                \\\"guid\\\": \\\"8089edbf-36ba-4bc8-a78d-f66e7614eb56\\\",\\n                \\\"src_subset\\\": {\\n                  \\\"type\\\": \\\"Range\\\",\\n                  \\\"ranges\\\": [\\n                    {\\n                      \\\"start\\\": \\\"__i0\\\",\\n                      \\\"end\\\": \\\"__i0\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    },\\n                    {\\n                      \\\"start\\\": \\\"__i1\\\",\\n                      \\\"end\\\": \\\"__i1\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    }\\n                  ]\\n                },\\n                \\\"dst_subset\\\": null,\\n                \\\"is_data_src\\\": true,\\n                \\\"num_accesses\\\": \\\"1\\\"\\n              }\\n            }\\n          },\\n          \\\"src\\\": \\\"6\\\",\\n          \\\"dst\\\": \\\"0\\\",\\n          \\\"dst_connector\\\": \\\"__in2\\\",\\n          \\\"src_connector\\\": \\\"OUT_1\\\"\\n        },\\n        {\\n          \\\"type\\\": \\\"MultiConnectorEdge\\\",\\n          \\\"attributes\\\": {\\n            \\\"data\\\": {\\n              \\\"type\\\": \\\"Memlet\\\",\\n              \\\"attributes\\\": {\\n                \\\"volume\\\": \\\"1\\\",\\n                \\\"subset\\\": {\\n                  \\\"type\\\": \\\"Range\\\",\\n                  \\\"ranges\\\": [\\n                    {\\n                      \\\"start\\\": \\\"__i0\\\",\\n                      \\\"end\\\": \\\"__i0\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    },\\n                    {\\n                      \\\"start\\\": \\\"__i1\\\",\\n                      \\\"end\\\": \\\"__i1\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    }\\n                  ]\\n                },\\n                \\\"data\\\": \\\"A\\\",\\n                \\\"debuginfo\\\": null,\\n                \\\"guid\\\": \\\"842edf23-5bb3-4dfa-b263-362e357ca94f\\\",\\n                \\\"src_subset\\\": {\\n                  \\\"type\\\": \\\"Range\\\",\\n                  \\\"ranges\\\": [\\n                    {\\n                      \\\"start\\\": \\\"__i0\\\",\\n                      \\\"end\\\": \\\"__i0\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    },\\n                    {\\n                      \\\"start\\\": \\\"__i1\\\",\\n                      \\\"end\\\": \\\"__i1\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    }\\n                  ]\\n                },\\n                \\\"dst_subset\\\": null,\\n                \\\"is_data_src\\\": true,\\n                \\\"num_accesses\\\": \\\"1\\\"\\n              }\\n            }\\n          },\\n          \\\"src\\\": \\\"6\\\",\\n          \\\"dst\\\": \\\"3\\\",\\n          \\\"dst_connector\\\": \\\"__in1\\\",\\n          \\\"src_connector\\\": \\\"OUT_2\\\"\\n        },\\n        {\\n          \\\"type\\\": \\\"MultiConnectorEdge\\\",\\n          \\\"attributes\\\": {\\n            \\\"data\\\": {\\n              \\\"type\\\": \\\"Memlet\\\",\\n              \\\"attributes\\\": {\\n                \\\"volume\\\": \\\"1\\\",\\n                \\\"subset\\\": {\\n                  \\\"type\\\": \\\"Range\\\",\\n                  \\\"ranges\\\": [\\n                    {\\n                      \\\"start\\\": \\\"0\\\",\\n                      \\\"end\\\": \\\"0\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    },\\n                    {\\n                      \\\"start\\\": \\\"0\\\",\\n                      \\\"end\\\": \\\"0\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    }\\n                  ]\\n                },\\n                \\\"data\\\": \\\"__tmp0\\\",\\n                \\\"debuginfo\\\": null,\\n                \\\"guid\\\": \\\"d4f88997-5e97-4bb5-b33a-8565655b3ddb\\\",\\n                \\\"src_subset\\\": null,\\n                \\\"dst_subset\\\": {\\n                  \\\"type\\\": \\\"Range\\\",\\n                  \\\"ranges\\\": [\\n                    {\\n                      \\\"start\\\": \\\"0\\\",\\n                      \\\"end\\\": \\\"0\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    },\\n                    {\\n                      \\\"start\\\": \\\"0\\\",\\n                      \\\"end\\\": \\\"0\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    }\\n                  ]\\n                },\\n                \\\"is_data_src\\\": false,\\n                \\\"num_accesses\\\": \\\"1\\\"\\n              }\\n            }\\n          },\\n          \\\"src\\\": \\\"0\\\",\\n          \\\"dst\\\": \\\"2\\\",\\n          \\\"dst_connector\\\": null,\\n          \\\"src_connector\\\": \\\"__out\\\"\\n        },\\n        {\\n          \\\"type\\\": \\\"MultiConnectorEdge\\\",\\n          \\\"attributes\\\": {\\n            \\\"data\\\": {\\n              \\\"type\\\": \\\"Memlet\\\",\\n              \\\"attributes\\\": {\\n                \\\"volume\\\": \\\"1\\\",\\n                \\\"subset\\\": {\\n                  \\\"type\\\": \\\"Range\\\",\\n                  \\\"ranges\\\": [\\n                    {\\n                      \\\"start\\\": \\\"__i0\\\",\\n                      \\\"end\\\": \\\"__i0\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    },\\n                    {\\n                      \\\"start\\\": \\\"__i1\\\",\\n                      \\\"end\\\": \\\"__i1\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    }\\n                  ]\\n                },\\n                \\\"data\\\": \\\"__return\\\",\\n                \\\"debuginfo\\\": null,\\n                \\\"guid\\\": \\\"9fa3de7c-66e4-4c1a-a7f8-5cbbdfe46c78\\\",\\n                \\\"src_subset\\\": null,\\n                \\\"dst_subset\\\": {\\n                  \\\"type\\\": \\\"Range\\\",\\n                  \\\"ranges\\\": [\\n                    {\\n                      \\\"start\\\": \\\"__i0\\\",\\n                      \\\"end\\\": \\\"__i0\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    },\\n                    {\\n                      \\\"start\\\": \\\"__i1\\\",\\n                      \\\"end\\\": \\\"__i1\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    }\\n                  ]\\n                },\\n                \\\"is_data_src\\\": false,\\n                \\\"num_accesses\\\": \\\"1\\\"\\n              }\\n            }\\n          },\\n          \\\"src\\\": \\\"3\\\",\\n          \\\"dst\\\": \\\"7\\\",\\n          \\\"dst_connector\\\": \\\"IN_1\\\",\\n          \\\"src_connector\\\": \\\"__out\\\"\\n        }\\n      ],\\n      \\\"attributes\\\": {\\n        \\\"executions\\\": \\\"1\\\",\\n        \\\"dynamic_executions\\\": false,\\n        \\\"guid\\\": \\\"db8eab8a-a9bc-49ab-b36a-bec13c4347ff\\\"\\n      }\\n    }\\n  ],\\n  \\\"edges\\\": [],\\n  \\\"collapsed\\\": false,\\n  \\\"label\\\": \\\"\\\",\\n  \\\"id\\\": null,\\n  \\\"cfg_list_id\\\": 0,\\n  \\\"start_block\\\": 0,\\n  \\\"dace_version\\\": \\\"0.16.1\\\"\\n}\";\n",
        "</script>\n",
        "<script>\n",
-       "    var sdfv_6742868030833812677 = new SDFV();\n",
-       "    var renderer_6742868030833812677 = new SDFGRenderer(sdfv_6742868030833812677, parse_sdfg(sdfg_6742868030833812677),\n",
-       "        document.getElementById('contents_6742868030833812677'));\n",
+       "    new SDFGRenderer(\n",
+       "        checkCompatLoad(parse_sdfg(sdfg_6451107013997515088)),\n",
+       "        document.getElementById(\"contents_6451107013997515088\"),\n",
+       "        undefined, null, null, false, null, null\n",
+       "    );\n",
        "</script>"
       ],
       "text/plain": [
@@ -456,30 +468,22 @@
       "4. Transformation GPUTransformLocalStorage in outer_fused[__i0=0:1000, __i1=0:1000]\n",
       "5. Transformation GPUTransformMap in outer_fused[__i0=0:1000, __i1=0:1000]\n",
       "6. Transformation GPUTransformSDFG in []\n",
-      "7. Transformation MapDimShuffle in [MapEntry (outer_fused[__i0=0:1000, __i1=0:1000])]\n",
-      "8. Transformation MapExpansion in [MapEntry (outer_fused[__i0=0:1000, __i1=0:1000])]\n",
-      "9. Transformation MapFission in [MapEntry (outer_fused[__i0=0:1000, __i1=0:1000])]\n",
-      "10. Transformation MapTiling in [MapEntry (outer_fused[__i0=0:1000, __i1=0:1000])]\n",
-      "11. Transformation MapTilingWithOverlap in [MapEntry (outer_fused[__i0=0:1000, __i1=0:1000])]\n",
-      "12. Transformation MapUnroll in [MapEntry (outer_fused[__i0=0:1000, __i1=0:1000])]\n",
-      "13. Transformation NestSDFG in []\n",
-      "14. Transformation ReductionNOperation in [MapEntry (outer_fused[__i0=0:1000, __i1=0:1000])]\n",
-      "15. Transformation StripMining in outer_fused: ['__i0', '__i1']\n",
-      "16. Transformation TaskletFusion in [Tasklet (_Mult_), AccessNode (__tmp0), Tasklet (_Add_)]\n"
-     ]
-    },
-    {
-     "name": "stdin",
-     "output_type": "stream",
-     "text": [
-      "Select the pattern to apply (0 - 16 or name$id):  MapExpansion$0\n"
+      "7. Transformation MapExpansion in [MapEntry (outer_fused[__i0=0:1000, __i1=0:1000])]\n",
+      "8. Transformation MapFission in [MapEntry (outer_fused[__i0=0:1000, __i1=0:1000])]\n",
+      "9. Transformation MapTiling in [MapEntry (outer_fused[__i0=0:1000, __i1=0:1000])]\n",
+      "10. Transformation MapTilingWithOverlap in [MapEntry (outer_fused[__i0=0:1000, __i1=0:1000])]\n",
+      "11. Transformation MapUnroll in [MapEntry (outer_fused[__i0=0:1000, __i1=0:1000])]\n",
+      "12. Transformation NestSDFG in []\n",
+      "13. Transformation ReductionNOperation in [MapEntry (outer_fused[__i0=0:1000, __i1=0:1000])]\n",
+      "14. Transformation StripMining in outer_fused: ['__i0', '__i1']\n",
+      "15. Transformation TaskletFusion in [Tasklet (_Mult_), AccessNode (__tmp0), Tasklet (_Add_)]\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "You selected (MapExpansion$0) pattern MapExpansion in [MapEntry (outer_fused[__i0=0:1000, __i1=0:1000])] with parameters {}\n",
+      "You selected (7) pattern MapExpansion in [MapEntry (outer_fused[__i0=0:1000, __i1=0:1000])] with parameters {}\n",
       "0. Transformation ElementWiseArrayOperation in [MapEntry (outer_fused___i1[__i1=0:1000])]\n",
       "1. Transformation FPGATransformSDFG in []\n",
       "2. Transformation FPGATransformState in [SDFGState (BinOp_5)]\n",
@@ -491,88 +495,63 @@
       "8. Transformation InLocalStorage in outer_fused[__i0=0:1000] -> outer_fused___i1[__i1=0:1000]\n",
       "9. Transformation MPITransformMap in [MapEntry (outer_fused[__i0=0:1000])]\n",
       "10. Transformation MPITransformMap in [MapEntry (outer_fused___i1[__i1=0:1000])]\n",
-      "11. Transformation MapDimShuffle in [MapEntry (outer_fused[__i0=0:1000])]\n",
-      "12. Transformation MapDimShuffle in [MapEntry (outer_fused___i1[__i1=0:1000])]\n",
-      "13. Transformation MapFission in [MapEntry (outer_fused___i1[__i1=0:1000])]\n",
-      "14. Transformation MapInterchange in [MapEntry (outer_fused[__i0=0:1000]), MapEntry (outer_fused___i1[__i1=0:1000])]\n",
-      "15. Transformation MapTiling in [MapEntry (outer_fused[__i0=0:1000])]\n",
-      "16. Transformation MapTiling in [MapEntry (outer_fused___i1[__i1=0:1000])]\n",
-      "17. Transformation MapTilingWithOverlap in [MapEntry (outer_fused[__i0=0:1000])]\n",
-      "18. Transformation MapTilingWithOverlap in [MapEntry (outer_fused___i1[__i1=0:1000])]\n",
-      "19. Transformation MapToForLoop in [MapEntry (outer_fused[__i0=0:1000])]\n",
-      "20. Transformation MapToForLoop in [MapEntry (outer_fused___i1[__i1=0:1000])]\n",
+      "11. Transformation MapFission in [MapEntry (outer_fused___i1[__i1=0:1000])]\n",
+      "12. Transformation MapInterchange in [MapEntry (outer_fused[__i0=0:1000]), MapEntry (outer_fused___i1[__i1=0:1000])]\n",
+      "13. Transformation MapTiling in [MapEntry (outer_fused[__i0=0:1000])]\n",
+      "14. Transformation MapTiling in [MapEntry (outer_fused___i1[__i1=0:1000])]\n",
+      "15. Transformation MapTilingWithOverlap in [MapEntry (outer_fused[__i0=0:1000])]\n",
+      "16. Transformation MapTilingWithOverlap in [MapEntry (outer_fused___i1[__i1=0:1000])]\n",
+      "17. Transformation MapToForLoop in [MapEntry (outer_fused[__i0=0:1000])]\n",
+      "18. Transformation MapToForLoop in [MapEntry (outer_fused___i1[__i1=0:1000])]\n",
+      "19. Transformation MapToForLoopRegion in [MapEntry (outer_fused[__i0=0:1000])]\n",
+      "20. Transformation MapToForLoopRegion in [MapEntry (outer_fused___i1[__i1=0:1000])]\n",
       "21. Transformation MapUnroll in [MapEntry (outer_fused[__i0=0:1000])]\n",
       "22. Transformation NestSDFG in []\n",
       "23. Transformation OutLocalStorage in outer_fused___i1[__i1=0:1000] -> outer_fused[__i0=0:1000]\n",
       "24. Transformation ReductionNOperation in [MapEntry (outer_fused___i1[__i1=0:1000])]\n",
       "25. Transformation StripMining in outer_fused: ['__i0']\n",
       "26. Transformation StripMining in outer_fused___i1: ['__i1']\n",
-      "27. Transformation TaskletFusion in [Tasklet (_Mult_), AccessNode (__tmp0), Tasklet (_Add_)]\n"
-     ]
-    },
-    {
-     "name": "stdin",
-     "output_type": "stream",
-     "text": [
-      "Select the pattern to apply (0 - 27 or name$id):  MapTiling$0(tile_sizes=(128,))\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "You selected (MapTiling$0) pattern MapTiling in [MapEntry (outer_fused[__i0=0:1000])] with parameters {'tile_sizes': (128,)}\n",
-      "0. Transformation ElementWiseArrayOperation in [MapEntry (outer_fused___i1[__i1=0:1000])]\n",
-      "1. Transformation FPGATransformSDFG in []\n",
-      "2. Transformation FPGATransformState in [SDFGState (BinOp_5)]\n",
-      "3. Transformation GPUGridStridedTiling in [MapEntry (outer_fused[__i0=tile___i0:Min(999, tile___i0 + 127) + 1]), MapEntry (outer_fused___i1[__i1=0:1000])]\n",
-      "4. Transformation GPUGridStridedTiling in [MapEntry (outer_fused[tile___i0=0:1000:128]), MapEntry (outer_fused[__i0=tile___i0:Min(999, tile___i0 + 127) + 1])]\n",
-      "5. Transformation GPUTransformLocalStorage in outer_fused[tile___i0=0:1000:128]\n",
-      "6. Transformation GPUTransformMap in outer_fused[__i0=tile___i0:Min(999, tile___i0 + 127) + 1]\n",
-      "7. Transformation GPUTransformMap in outer_fused___i1[__i1=0:1000]\n",
-      "8. Transformation GPUTransformMap in outer_fused[tile___i0=0:1000:128]\n",
+      "27. Transformation TaskletFusion in [Tasklet (_Mult_), AccessNode (__tmp0), Tasklet (_Add_)]\n",
+      "You selected (11) pattern MapFission in [MapEntry (outer_fused___i1[__i1=0:1000])] with parameters {}\n",
+      "0. Transformation BufferTiling in [MapExit (outer_fused___i1_fission[__i1=0:1000]), AccessNode (__tmp0), MapEntry (outer_fused___i1_fission[__i1=0:1000])]\n",
+      "1. Transformation ElementWiseArrayOperation in [MapEntry (outer_fused___i1_fission[__i1=0:1000])]\n",
+      "2. Transformation ElementWiseArrayOperation in [MapEntry (outer_fused___i1_fission[__i1=0:1000])]\n",
+      "3. Transformation FPGATransformSDFG in []\n",
+      "4. Transformation FPGATransformState in [SDFGState (BinOp_5)]\n",
+      "5. Transformation GPUTransformLocalStorage in outer_fused[__i0=0:1000]\n",
+      "6. Transformation GPUTransformMap in outer_fused[__i0=0:1000]\n",
+      "7. Transformation GPUTransformMap in outer_fused___i1_fission[__i1=0:1000]\n",
+      "8. Transformation GPUTransformMap in outer_fused___i1_fission[__i1=0:1000]\n",
       "9. Transformation GPUTransformSDFG in []\n",
-      "10. Transformation InLocalStorage in outer_fused[__i0=tile___i0:Min(999, tile___i0 + 127) + 1] -> outer_fused___i1[__i1=0:1000]\n",
-      "11. Transformation InLocalStorage in outer_fused[tile___i0=0:1000:128] -> outer_fused[__i0=tile___i0:Min(999, tile___i0 + 127) + 1]\n",
-      "12. Transformation MPITransformMap in [MapEntry (outer_fused[__i0=tile___i0:Min(999, tile___i0 + 127) + 1])]\n",
-      "13. Transformation MPITransformMap in [MapEntry (outer_fused___i1[__i1=0:1000])]\n",
-      "14. Transformation MPITransformMap in [MapEntry (outer_fused[tile___i0=0:1000:128])]\n",
-      "15. Transformation MapDimShuffle in [MapEntry (outer_fused[__i0=tile___i0:Min(999, tile___i0 + 127) + 1])]\n",
-      "16. Transformation MapDimShuffle in [MapEntry (outer_fused___i1[__i1=0:1000])]\n",
-      "17. Transformation MapDimShuffle in [MapEntry (outer_fused[tile___i0=0:1000:128])]\n",
-      "18. Transformation MapFission in [MapEntry (outer_fused___i1[__i1=0:1000])]\n",
-      "19. Transformation MapInterchange in [MapEntry (outer_fused[__i0=tile___i0:Min(999, tile___i0 + 127) + 1]), MapEntry (outer_fused___i1[__i1=0:1000])]\n",
-      "20. Transformation MapTiling in [MapEntry (outer_fused[__i0=tile___i0:Min(999, tile___i0 + 127) + 1])]\n",
-      "21. Transformation MapTiling in [MapEntry (outer_fused___i1[__i1=0:1000])]\n",
-      "22. Transformation MapTiling in [MapEntry (outer_fused[tile___i0=0:1000:128])]\n",
-      "23. Transformation MapTilingWithOverlap in [MapEntry (outer_fused[__i0=tile___i0:Min(999, tile___i0 + 127) + 1])]\n",
-      "24. Transformation MapTilingWithOverlap in [MapEntry (outer_fused___i1[__i1=0:1000])]\n",
-      "25. Transformation MapTilingWithOverlap in [MapEntry (outer_fused[tile___i0=0:1000:128])]\n",
-      "26. Transformation MapToForLoop in [MapEntry (outer_fused[__i0=tile___i0:Min(999, tile___i0 + 127) + 1])]\n",
-      "27. Transformation MapToForLoop in [MapEntry (outer_fused___i1[__i1=0:1000])]\n",
-      "28. Transformation MapToForLoop in [MapEntry (outer_fused[tile___i0=0:1000:128])]\n",
-      "29. Transformation MapUnroll in [MapEntry (outer_fused[tile___i0=0:1000:128])]\n",
+      "10. Transformation InLocalStorage in outer_fused[__i0=0:1000] -> outer_fused___i1_fission[__i1=0:1000]\n",
+      "11. Transformation InLocalStorage in outer_fused[__i0=0:1000] -> outer_fused___i1_fission[__i1=0:1000]\n",
+      "12. Transformation MPITransformMap in [MapEntry (outer_fused[__i0=0:1000])]\n",
+      "13. Transformation MPITransformMap in [MapEntry (outer_fused___i1_fission[__i1=0:1000])]\n",
+      "14. Transformation MPITransformMap in [MapEntry (outer_fused___i1_fission[__i1=0:1000])]\n",
+      "15. Transformation MapFission in [MapEntry (outer_fused[__i0=0:1000])]\n",
+      "16. Transformation MapFusion in [MapExit (outer_fused___i1_fission[__i1=0:1000]), AccessNode (__tmp0), MapEntry (outer_fused___i1_fission[__i1=0:1000])]\n",
+      "17. Transformation MapTiling in [MapEntry (outer_fused[__i0=0:1000])]\n",
+      "18. Transformation MapTiling in [MapEntry (outer_fused___i1_fission[__i1=0:1000])]\n",
+      "19. Transformation MapTiling in [MapEntry (outer_fused___i1_fission[__i1=0:1000])]\n",
+      "20. Transformation MapTilingWithOverlap in [MapEntry (outer_fused[__i0=0:1000])]\n",
+      "21. Transformation MapTilingWithOverlap in [MapEntry (outer_fused___i1_fission[__i1=0:1000])]\n",
+      "22. Transformation MapTilingWithOverlap in [MapEntry (outer_fused___i1_fission[__i1=0:1000])]\n",
+      "23. Transformation MapToForLoop in [MapEntry (outer_fused[__i0=0:1000])]\n",
+      "24. Transformation MapToForLoop in [MapEntry (outer_fused___i1_fission[__i1=0:1000])]\n",
+      "25. Transformation MapToForLoop in [MapEntry (outer_fused___i1_fission[__i1=0:1000])]\n",
+      "26. Transformation MapToForLoopRegion in [MapEntry (outer_fused[__i0=0:1000])]\n",
+      "27. Transformation MapToForLoopRegion in [MapEntry (outer_fused___i1_fission[__i1=0:1000])]\n",
+      "28. Transformation MapToForLoopRegion in [MapEntry (outer_fused___i1_fission[__i1=0:1000])]\n",
+      "29. Transformation MapUnroll in [MapEntry (outer_fused[__i0=0:1000])]\n",
       "30. Transformation NestSDFG in []\n",
-      "31. Transformation OutLocalStorage in outer_fused[__i0=tile___i0:Min(999, tile___i0 + 127) + 1] -> outer_fused[tile___i0=0:1000:128]\n",
-      "32. Transformation OutLocalStorage in outer_fused___i1[__i1=0:1000] -> outer_fused[__i0=tile___i0:Min(999, tile___i0 + 127) + 1]\n",
-      "33. Transformation ReductionNOperation in [MapEntry (outer_fused___i1[__i1=0:1000])]\n",
+      "31. Transformation OTFMapFusion in [MapExit (outer_fused___i1_fission[__i1=0:1000]), AccessNode (__tmp0), MapEntry (outer_fused___i1_fission[__i1=0:1000])]\n",
+      "32. Transformation OutLocalStorage in outer_fused___i1_fission[__i1=0:1000] -> outer_fused[__i0=0:1000]\n",
+      "33. Transformation ReductionNOperation in [MapEntry (outer_fused___i1_fission[__i1=0:1000])]\n",
       "34. Transformation StripMining in outer_fused: ['__i0']\n",
-      "35. Transformation StripMining in outer_fused___i1: ['__i1']\n",
-      "36. Transformation StripMining in outer_fused: ['tile___i0']\n",
-      "37. Transformation TaskletFusion in [Tasklet (_Mult_), AccessNode (__tmp0), Tasklet (_Add_)]\n"
-     ]
-    },
-    {
-     "name": "stdin",
-     "output_type": "stream",
-     "text": [
-      "Select the pattern to apply (0 - 37 or name$id):  \n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
+      "35. Transformation StripMining in outer_fused___i1_fission: ['__i1']\n",
+      "36. Transformation StripMining in outer_fused___i1_fission: ['__i1']\n",
+      "37. Transformation Vectorization in [MapEntry (outer_fused___i1_fission[__i1=0:1000])]\n",
+      "38. Transformation Vectorization in [MapEntry (outer_fused___i1_fission[__i1=0:1000])]\n",
       "You did not select a valid option. Quitting optimization ...\n"
      ]
     }
@@ -654,15 +633,17 @@
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        "\n",
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+       "<div id=\"contents_3342881732680440817\" style=\"position: relative; resize: vertical; overflow: auto\"></div>\n",
        "</div>\n",
        "<script>\n",
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        "<script>\n",
-       "    var sdfv_388863092910660824 = new SDFV();\n",
-       "    var renderer_388863092910660824 = new SDFGRenderer(sdfv_388863092910660824, parse_sdfg(sdfg_388863092910660824),\n",
-       "        document.getElementById('contents_388863092910660824'));\n",
+       "    new SDFGRenderer(\n",
+       "        checkCompatLoad(parse_sdfg(sdfg_3342881732680440817)),\n",
+       "        document.getElementById(\"contents_3342881732680440817\"),\n",
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\\\"OUT_1\\\"\\n        },\\n        {\\n          \\\"type\\\": \\\"MultiConnectorEdge\\\",\\n          \\\"attributes\\\": {\\n            \\\"data\\\": {\\n              \\\"type\\\": \\\"Memlet\\\",\\n              \\\"attributes\\\": {\\n                \\\"volume\\\": \\\"1000\\\",\\n                \\\"subset\\\": {\\n                  \\\"type\\\": \\\"Range\\\",\\n                  \\\"ranges\\\": [\\n                    {\\n                      \\\"start\\\": \\\"__i0\\\",\\n                      \\\"end\\\": \\\"__i0\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    },\\n                    {\\n                      \\\"start\\\": \\\"0\\\",\\n                      \\\"end\\\": \\\"999\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    }\\n                  ]\\n                },\\n                \\\"data\\\": \\\"B\\\",\\n                \\\"debuginfo\\\": null,\\n                \\\"guid\\\": \\\"c33fe3e5-661b-42e4-9670-61bcd8b35fc4\\\",\\n                \\\"src_subset\\\": {\\n                  \\\"type\\\": \\\"Range\\\",\\n                  \\\"ranges\\\": [\\n                    {\\n                      \\\"start\\\": \\\"__i0\\\",\\n                      \\\"end\\\": \\\"__i0\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    },\\n                    {\\n                      \\\"start\\\": \\\"0\\\",\\n                      \\\"end\\\": \\\"999\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    }\\n                  ]\\n                },\\n                \\\"dst_subset\\\": null,\\n                \\\"is_data_src\\\": true,\\n                \\\"num_accesses\\\": \\\"1000\\\"\\n              }\\n            }\\n          },\\n          \\\"src\\\": \\\"6\\\",\\n          \\\"dst\\\": \\\"8\\\",\\n          \\\"dst_connector\\\": \\\"IN_1\\\",\\n          \\\"src_connector\\\": \\\"OUT_1\\\"\\n        },\\n        {\\n          \\\"type\\\": \\\"MultiConnectorEdge\\\",\\n          \\\"attributes\\\": {\\n            \\\"data\\\": {\\n              \\\"type\\\": \\\"Memlet\\\",\\n              \\\"attributes\\\": {\\n                \\\"volume\\\": \\\"1\\\",\\n                \\\"subset\\\": {\\n                  \\\"type\\\": \\\"Range\\\",\\n                  \\\"ranges\\\": [\\n                    {\\n                      \\\"start\\\": \\\"__i0\\\",\\n                      \\\"end\\\": \\\"__i0\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    },\\n                    {\\n                      \\\"start\\\": \\\"__i1\\\",\\n                      \\\"end\\\": \\\"__i1\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    }\\n                  ]\\n                },\\n                \\\"data\\\": \\\"A\\\",\\n                \\\"debuginfo\\\": null,\\n                \\\"guid\\\": \\\"34da8fac-ff61-4a0b-a72d-d842bb917526\\\",\\n                \\\"src_subset\\\": {\\n                  \\\"type\\\": \\\"Range\\\",\\n                  \\\"ranges\\\": [\\n                    {\\n                      \\\"start\\\": \\\"__i0\\\",\\n                      \\\"end\\\": \\\"__i0\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    },\\n                    {\\n                      \\\"start\\\": \\\"__i1\\\",\\n                      \\\"end\\\": \\\"__i1\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    }\\n                  ]\\n                },\\n                \\\"dst_subset\\\": null,\\n                \\\"is_data_src\\\": true,\\n                \\\"num_accesses\\\": \\\"1\\\"\\n              }\\n            }\\n          },\\n          \\\"src\\\": \\\"10\\\",\\n          \\\"dst\\\": \\\"3\\\",\\n          \\\"dst_connector\\\": \\\"__in1\\\",\\n          \\\"src_connector\\\": \\\"OUT_1\\\"\\n        },\\n        {\\n          \\\"type\\\": \\\"MultiConnectorEdge\\\",\\n          \\\"attributes\\\": {\\n            \\\"data\\\": {\\n              \\\"type\\\": \\\"Memlet\\\",\\n              \\\"attributes\\\": {\\n                \\\"volume\\\": \\\"1\\\",\\n                \\\"subset\\\": {\\n                  \\\"type\\\": \\\"Range\\\",\\n                  \\\"ranges\\\": [\\n                    {\\n                      \\\"start\\\": \\\"__i0\\\",\\n                      \\\"end\\\": \\\"__i0\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    },\\n                    {\\n                      \\\"start\\\": \\\"__i1\\\",\\n                      \\\"end\\\": \\\"__i1\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    }\\n                  ]\\n                },\\n                \\\"data\\\": \\\"B\\\",\\n                \\\"debuginfo\\\": null,\\n                \\\"guid\\\": \\\"c33fe3e5-661b-42e4-9670-61bcd8b35fc4\\\",\\n                \\\"src_subset\\\": {\\n                  \\\"type\\\": \\\"Range\\\",\\n                  \\\"ranges\\\": [\\n                    {\\n                      \\\"start\\\": \\\"__i0\\\",\\n                      \\\"end\\\": \\\"__i0\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    },\\n                    {\\n                      \\\"start\\\": \\\"__i1\\\",\\n                      \\\"end\\\": \\\"__i1\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    }\\n                  ]\\n                },\\n                \\\"dst_subset\\\": null,\\n                \\\"is_data_src\\\": true,\\n                \\\"num_accesses\\\": \\\"1\\\"\\n              }\\n            }\\n          },\\n          \\\"src\\\": \\\"8\\\",\\n          \\\"dst\\\": \\\"0\\\",\\n          \\\"dst_connector\\\": \\\"__in2\\\",\\n          \\\"src_connector\\\": \\\"OUT_1\\\"\\n        },\\n        {\\n          \\\"type\\\": \\\"MultiConnectorEdge\\\",\\n          \\\"attributes\\\": {\\n            \\\"data\\\": {\\n              \\\"type\\\": \\\"Memlet\\\",\\n              \\\"attributes\\\": {\\n                \\\"volume\\\": \\\"1000\\\",\\n                \\\"subset\\\": {\\n                  \\\"type\\\": \\\"Range\\\",\\n                  \\\"ranges\\\": [\\n                    {\\n                      \\\"start\\\": \\\"__i0\\\",\\n                      \\\"end\\\": \\\"__i0\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    },\\n                    {\\n                      \\\"start\\\": \\\"0\\\",\\n                      \\\"end\\\": \\\"999\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    }\\n                  ]\\n                },\\n                \\\"data\\\": \\\"A\\\",\\n                \\\"debuginfo\\\": null,\\n                \\\"guid\\\": \\\"34da8fac-ff61-4a0b-a72d-d842bb917526\\\",\\n                \\\"src_subset\\\": {\\n                  \\\"type\\\": \\\"Range\\\",\\n                  \\\"ranges\\\": [\\n                    {\\n                      \\\"start\\\": \\\"__i0\\\",\\n                      \\\"end\\\": \\\"__i0\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    },\\n                    {\\n                      \\\"start\\\": \\\"0\\\",\\n                      \\\"end\\\": \\\"999\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    }\\n                  ]\\n                },\\n                \\\"dst_subset\\\": null,\\n                \\\"is_data_src\\\": true,\\n                \\\"num_accesses\\\": \\\"1000\\\"\\n              }\\n            }\\n          },\\n          \\\"src\\\": \\\"6\\\",\\n          \\\"dst\\\": \\\"10\\\",\\n          \\\"dst_connector\\\": \\\"IN_1\\\",\\n          \\\"src_connector\\\": \\\"OUT_2\\\"\\n        },\\n        {\\n          \\\"type\\\": \\\"MultiConnectorEdge\\\",\\n          \\\"attributes\\\": {\\n            \\\"data\\\": {\\n              \\\"type\\\": \\\"Memlet\\\",\\n              \\\"attributes\\\": {\\n                \\\"volume\\\": \\\"1\\\",\\n                \\\"subset\\\": {\\n                  \\\"type\\\": \\\"Range\\\",\\n                  \\\"ranges\\\": [\\n                    {\\n                      \\\"start\\\": \\\"__i1\\\",\\n                      \\\"end\\\": \\\"__i1\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    },\\n                    {\\n                      \\\"start\\\": \\\"0\\\",\\n                      \\\"end\\\": \\\"0\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    },\\n                    {\\n                      \\\"start\\\": \\\"0\\\",\\n                      \\\"end\\\": \\\"0\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    }\\n                  ]\\n                },\\n                \\\"data\\\": \\\"__tmp0\\\",\\n                \\\"debuginfo\\\": null,\\n                \\\"guid\\\": \\\"626b7456-accd-41c7-a76a-140e7f81aa0e\\\",\\n                \\\"src_subset\\\": null,\\n                \\\"dst_subset\\\": {\\n                  \\\"type\\\": \\\"Range\\\",\\n                  \\\"ranges\\\": [\\n                    {\\n                      \\\"start\\\": \\\"__i1\\\",\\n                      \\\"end\\\": \\\"__i1\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    },\\n                    {\\n                      \\\"start\\\": \\\"0\\\",\\n                      \\\"end\\\": \\\"0\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    },\\n                    {\\n                      \\\"start\\\": \\\"0\\\",\\n                      \\\"end\\\": \\\"0\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    }\\n                  ]\\n                },\\n                \\\"is_data_src\\\": false,\\n                \\\"num_accesses\\\": \\\"1\\\"\\n              }\\n            }\\n          },\\n          \\\"src\\\": \\\"0\\\",\\n          \\\"dst\\\": \\\"9\\\",\\n          \\\"dst_connector\\\": \\\"IN_0\\\",\\n          \\\"src_connector\\\": \\\"__out\\\"\\n        },\\n        {\\n          \\\"type\\\": \\\"MultiConnectorEdge\\\",\\n          \\\"attributes\\\": {\\n            \\\"data\\\": {\\n              \\\"type\\\": \\\"Memlet\\\",\\n              \\\"attributes\\\": {\\n                \\\"volume\\\": \\\"1\\\",\\n                \\\"subset\\\": {\\n                  \\\"type\\\": \\\"Range\\\",\\n                  \\\"ranges\\\": [\\n                    {\\n                      \\\"start\\\": \\\"__i0\\\",\\n                      \\\"end\\\": \\\"__i0\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    },\\n                    {\\n                      \\\"start\\\": \\\"__i1\\\",\\n                      \\\"end\\\": \\\"__i1\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    }\\n                  ]\\n                },\\n                \\\"data\\\": \\\"__return\\\",\\n                \\\"debuginfo\\\": null,\\n                \\\"guid\\\": \\\"0e629241-adfa-417b-86dd-46543cbd9d33\\\",\\n                \\\"src_subset\\\": null,\\n                \\\"dst_subset\\\": {\\n                  \\\"type\\\": \\\"Range\\\",\\n                  \\\"ranges\\\": [\\n                    {\\n                      \\\"start\\\": \\\"__i0\\\",\\n                      \\\"end\\\": \\\"__i0\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    },\\n                    {\\n                      \\\"start\\\": \\\"__i1\\\",\\n                      \\\"end\\\": \\\"__i1\\\",\\n                      \\\"step\\\": \\\"1\\\",\\n                      \\\"tile\\\": \\\"1\\\"\\n                    }\\n                  ]\\n                },\\n                \\\"is_data_src\\\": false,\\n                \\\"num_accesses\\\": \\\"1\\\"\\n              }\\n            }\\n          },\\n          \\\"src\\\": \\\"3\\\",\\n          \\\"dst\\\": \\\"11\\\",\\n          \\\"dst_connector\\\": \\\"IN_0\\\",\\n          \\\"src_connector\\\": \\\"__out\\\"\\n        }\\n      ],\\n      \\\"attributes\\\": {\\n        \\\"executions\\\": \\\"1\\\",\\n        \\\"dynamic_executions\\\": false,\\n        \\\"guid\\\": \\\"db8eab8a-a9bc-49ab-b36a-bec13c4347ff\\\"\\n      }\\n    }\\n  ],\\n  \\\"edges\\\": [],\\n  \\\"collapsed\\\": false,\\n  \\\"label\\\": \\\"\\\",\\n  \\\"id\\\": null,\\n  \\\"cfg_list_id\\\": 0,\\n  \\\"start_block\\\": 0,\\n  \\\"dace_version\\\": \\\"0.16.1\\\"\\n}\";\n",
        "</script>\n",
        "<script>\n",
-       "    var sdfv_4968806959259906985 = new SDFV();\n",
-       "    var renderer_4968806959259906985 = new SDFGRenderer(sdfv_4968806959259906985, parse_sdfg(sdfg_4968806959259906985),\n",
-       "        document.getElementById('contents_4968806959259906985'));\n",
+       "    new SDFGRenderer(\n",
+       "        checkCompatLoad(parse_sdfg(sdfg_675276908435406949)),\n",
+       "        document.getElementById(\"contents_675276908435406949\"),\n",
+       "        undefined, null, null, false, null, null\n",
+       "    );\n",
        "</script>"
       ],
       "text/plain": [
@@ -864,7 +847,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "dace_dev",
    "language": "python",
    "name": "python3"
   },
@@ -878,7 +861,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.1"
+   "version": "3.12.0"
   }
  },
  "nbformat": 4,

From 9dd70bb02f676acefd8ebec7f136abb6f0009d25 Mon Sep 17 00:00:00 2001
From: Roman Cattaneo <romanc@users.noreply.github.com>
Date: Fri, 1 Nov 2024 17:01:00 +0100
Subject: [PATCH 08/33] Fix broken codegen tutorial (#1720)

Quick fix follow-up from https://github.com/spcl/dace/pull/1706 which
left a broken notebook.

Co-authored-by: Roman Cattaneo <>
---
 tutorials/codegen.ipynb | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/tutorials/codegen.ipynb b/tutorials/codegen.ipynb
index 2c79f1a2e0..84b2cf7f01 100644
--- a/tutorials/codegen.ipynb
+++ b/tutorials/codegen.ipynb
@@ -497,8 +497,8 @@
     "                       function_stream: CodeIOStream, callsite_stream: CodeIOStream):\n",
     "        # The parameters here are:\n",
     "        # sdfg: The SDFG we are currently generating.\n",
-    "        # cfg: The current control flow graph (CFG) we are currently generating. For example,
-    "               it can be the SDFG or a loop region.
+    "        # cfg: The current control flow graph (CFG) we are currently generating. For example\n",
+    "        #      it can be the SDFG or a loop region.\n",
     "        # scope: The subgraph of the state containing only the scope (map contents)\n",
     "        #        we want to generate the code for.\n",
     "        # state_id: The state in the SDFG the subgraph is taken from (i.e.,\n",

From 2c414919ad31f486e86fe9ac685035c4c3c04fc9 Mon Sep 17 00:00:00 2001
From: Roman Cattaneo <romanc@users.noreply.github.com>
Date: Fri, 1 Nov 2024 18:51:20 +0100
Subject: [PATCH 09/33] CI: Update checkout and setup-python actions (#1718)

GitHub Actions workflows use outdated versions of

- actions/checkout
- actions/setup-python

These actions are built for specific node versions, which are now end of
life. While the workflows continue to run, GitHub issues a warning
(visible in the online interface) and runs them with newer versions of
node.


![image](https://github.com/user-attachments/assets/159f4d86-33f5-4d9c-ad45-a5657ad51a57)

Since both, checkout and setup-python, are basic actions, none of the
features that DaCe workflows are using changed. We might see slight
speedup from out of the box caching added to setup-python in recent
versions.

Parent issue: https://github.com/GEOS-ESM/SMT-Nebulae/issues/89

Co-authored-by: Roman Cattaneo <>
---
 .github/workflows/fpga-ci.yml                 | 2 +-
 .github/workflows/general-ci.yml              | 4 ++--
 .github/workflows/gpu-ci.yml                  | 2 +-
 .github/workflows/hardware_test.yml           | 2 +-
 .github/workflows/heterogeneous-ci.yml        | 2 +-
 .github/workflows/pyFV3-ci.yml                | 6 +++---
 .github/workflows/verilator_compatibility.yml | 4 ++--
 7 files changed, 11 insertions(+), 11 deletions(-)

diff --git a/.github/workflows/fpga-ci.yml b/.github/workflows/fpga-ci.yml
index ef8e5348da..2d6d42514f 100644
--- a/.github/workflows/fpga-ci.yml
+++ b/.github/workflows/fpga-ci.yml
@@ -16,7 +16,7 @@ jobs:
     if: ${{ !contains(github.event.pull_request.labels.*.name, 'no-ci') }}
     runs-on: [self-hosted, linux, intel-fpga, xilinx-fpga]
     steps:
-    - uses: actions/checkout@v2
+    - uses: actions/checkout@v4
       with:
         submodules: 'recursive'
     - name: Install dependencies
diff --git a/.github/workflows/general-ci.yml b/.github/workflows/general-ci.yml
index faf0a727be..2044639e5f 100644
--- a/.github/workflows/general-ci.yml
+++ b/.github/workflows/general-ci.yml
@@ -18,11 +18,11 @@ jobs:
         simplify: [0,1,autoopt]
 
     steps:
-    - uses: actions/checkout@v2
+    - uses: actions/checkout@v4
       with:
         submodules: 'recursive'
     - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v2
+      uses: actions/setup-python@v5
       with:
         python-version: ${{ matrix.python-version }}
     - name: Install dependencies
diff --git a/.github/workflows/gpu-ci.yml b/.github/workflows/gpu-ci.yml
index 527e004478..b3af9c8c05 100644
--- a/.github/workflows/gpu-ci.yml
+++ b/.github/workflows/gpu-ci.yml
@@ -19,7 +19,7 @@ jobs:
     if: "!contains(github.event.pull_request.labels.*.name, 'no-ci')"
     runs-on: [self-hosted, gpu]
     steps:
-    - uses: actions/checkout@v2
+    - uses: actions/checkout@v4
       with:
         submodules: 'recursive'
     - name: Install dependencies
diff --git a/.github/workflows/hardware_test.yml b/.github/workflows/hardware_test.yml
index 3fe32aaab7..e319c72587 100644
--- a/.github/workflows/hardware_test.yml
+++ b/.github/workflows/hardware_test.yml
@@ -4,7 +4,7 @@ jobs:
   test-rtl:
     runs-on: [self-hosted, linux, xilinx-fpga]
     steps:
-    - uses: actions/checkout@v2
+    - uses: actions/checkout@v4
       with:
         submodules: 'recursive'
     - name: Install dependencies
diff --git a/.github/workflows/heterogeneous-ci.yml b/.github/workflows/heterogeneous-ci.yml
index 99b566e21f..62887ad208 100644
--- a/.github/workflows/heterogeneous-ci.yml
+++ b/.github/workflows/heterogeneous-ci.yml
@@ -19,7 +19,7 @@ jobs:
     if: "!contains(github.event.pull_request.labels.*.name, 'no-ci')"
     runs-on: [self-hosted, linux]
     steps:
-    - uses: actions/checkout@v2
+    - uses: actions/checkout@v4
       with:
         submodules: 'recursive'
     - name: Install dependencies
diff --git a/.github/workflows/pyFV3-ci.yml b/.github/workflows/pyFV3-ci.yml
index f58fdf85ac..85c864e475 100644
--- a/.github/workflows/pyFV3-ci.yml
+++ b/.github/workflows/pyFV3-ci.yml
@@ -21,18 +21,18 @@ jobs:
               python-version: [3.11.7]
 
       steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v4
         with:
               repository: 'NOAA-GFDL/PyFV3'
               ref: 'ci/DaCe'
               submodules: 'recursive'
               path: 'pyFV3'
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v4
         with: 
             path: 'dace'
             submodules: 'recursive'
       - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v2
+        uses: actions/setup-python@v5
         with:
               python-version: ${{ matrix.python-version }}
       - name: Install library dependencies
diff --git a/.github/workflows/verilator_compatibility.yml b/.github/workflows/verilator_compatibility.yml
index 7f43565812..dce0c9b1fb 100644
--- a/.github/workflows/verilator_compatibility.yml
+++ b/.github/workflows/verilator_compatibility.yml
@@ -17,14 +17,14 @@ jobs:
     steps:
       - name: trigger reason
         run: echo "Trigger Reason:" ${{ github.event.inputs.reason }}
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v4
       - name: checkout submodules
         run: git submodule update --init --recursive
       - name: install apt packages
         run: sudo apt-get update && sudo apt-get -y install git make autoconf g++ flex bison libfl2 libfl-dev
       - name: compile verilator
         run: git clone https://github.com/verilator/verilator.git && cd verilator && git fetch origin && if [ ! "${{ matrix.verilator_version }}" == "master" ]; then  git checkout v${{ matrix.verilator_version }}; fi && autoconf && ./configure && make -j2 && sudo make install
-      - uses: actions/setup-python@v2
+      - uses: actions/setup-python@v5
         with:
           python-version: '3.8'
           architecture: 'x64'

From 636811dcacf768b4b8817c55f5e7f0eabb87973c Mon Sep 17 00:00:00 2001
From: Tal Ben-Nun <tbennun@users.noreply.github.com>
Date: Fri, 1 Nov 2024 21:03:52 -0700
Subject: [PATCH 10/33] Bump version and update dependencies (#1722)

Removes websockets dependency and makes jinja2 dependency optional
---
 dace/cli/dacelab.py   |  5 -----
 dace/cli/sdfg_diff.py |  6 +++++-
 dace/cli/sdfv.py      |  6 +++++-
 dace/version.py       |  2 +-
 requirements.txt      | 25 ++++++++-----------------
 setup.py              |  2 +-
 6 files changed, 20 insertions(+), 26 deletions(-)

diff --git a/dace/cli/dacelab.py b/dace/cli/dacelab.py
index 27a3215e09..647ec31a3d 100644
--- a/dace/cli/dacelab.py
+++ b/dace/cli/dacelab.py
@@ -2,11 +2,6 @@
 # Copyright 2019-2021 ETH Zurich and the DaCe authors. All rights reserved.
 
 import argparse
-import numpy
-import pickle
-import json
-
-import dace
 from dace.frontend.octave import parse
 from dace.sdfg.nodes import AccessNode
 
diff --git a/dace/cli/sdfg_diff.py b/dace/cli/sdfg_diff.py
index 9c40e59f10..2ec0a3adf4 100644
--- a/dace/cli/sdfg_diff.py
+++ b/dace/cli/sdfg_diff.py
@@ -9,7 +9,6 @@
 import tempfile
 from typing import Dict, Literal, Set, Tuple, Union
 
-import jinja2
 import dace
 from dace import memlet as mlt
 from dace.sdfg import nodes as nd
@@ -179,6 +178,11 @@ def main():
     diff_sets = _sdfg_diff(sdfg_A, sdfg_B, eq_strategy)
 
     if args.graphical:
+        try:
+            import jinja2
+        except (ImportError, ModuleNotFoundError):
+            raise ImportError('Graphical SDFG diff requires jinja2, please install by running `pip install jinja2`')
+
         basepath = os.path.join(os.path.dirname(os.path.realpath(dace.__file__)), 'viewer')
         template_loader = jinja2.FileSystemLoader(searchpath=os.path.join(basepath, 'templates'))
         template_env = jinja2.Environment(loader=template_loader)
diff --git a/dace/cli/sdfv.py b/dace/cli/sdfv.py
index 49255a1e7e..2012debe82 100644
--- a/dace/cli/sdfv.py
+++ b/dace/cli/sdfv.py
@@ -13,7 +13,6 @@
 
 import dace
 import tempfile
-import jinja2
 
 
 def partialclass(cls, *args, **kwds):
@@ -48,6 +47,11 @@ def view(sdfg: dace.SDFG, filename: Optional[Union[str, int]] = None, verbose: b
             os.close(fd)
             return
 
+    try:
+        import jinja2
+    except (ImportError, ModuleNotFoundError):
+        raise ImportError('SDFG.view() requires jinja2, please install by running `pip install jinja2`')
+
     if type(sdfg) is dace.SDFG:
         sdfg = dace.serialize.dumps(sdfg.to_json())
 
diff --git a/dace/version.py b/dace/version.py
index 9513287c94..1f356cc57b 100644
--- a/dace/version.py
+++ b/dace/version.py
@@ -1 +1 @@
-__version__ = '0.16.1'
+__version__ = '1.0.0'
diff --git a/requirements.txt b/requirements.txt
index 3cc37cc468..b902968b73 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,21 +1,12 @@
-aenum==3.1.12
+aenum==3.1.15
 astunparse==1.6.3
-certifi==2024.7.4
-charset-normalizer==3.1.0
-click==8.1.3
-dill==0.3.6
-fparser==0.1.3
-idna==3.7
-importlib-metadata==6.6.0
-Jinja2==3.1.4
-MarkupSafe==2.1.3
+dill==0.3.9
+fparser==0.1.4
 mpmath==1.3.0
-networkx==3.1
-numpy==1.26.1
+networkx==3.4.2
+numpy==1.26.4
+packaging==24.1
 ply==3.11
-PyYAML==6.0.1
+PyYAML==6.0.2
 six==1.16.0
-sympy==1.9
-urllib3==2.2.2
-websockets==11.0.3
-zipp==3.15.0
+sympy==1.13.3
diff --git a/setup.py b/setup.py
index 6e8635bdf6..c228ae4558 100644
--- a/setup.py
+++ b/setup.py
@@ -73,7 +73,7 @@
       },
       include_package_data=True,
       install_requires=[
-         'numpy < 2.0', 'networkx >= 2.5', 'astunparse', 'sympy >= 1.9', 'pyyaml', 'ply', 'websockets', 'jinja2',
+          'numpy < 2.0', 'networkx >= 2.5', 'astunparse', 'sympy >= 1.9', 'pyyaml', 'ply',
           'fparser >= 0.1.3', 'aenum >= 3.1', 'dataclasses; python_version < "3.7"', 'dill',
           'pyreadline;platform_system=="Windows"', 'typing-compat; python_version < "3.8"', 'packaging'
       ] + cmake_requires,

From b27024b57eeb679fe1326b00525228d581ca369e Mon Sep 17 00:00:00 2001
From: Philipp Schaad <schaad.phil@gmail.com>
Date: Mon, 4 Nov 2024 17:44:37 +0100
Subject: [PATCH 11/33] Various Cutout Fixes (#1662)

- [x] Fix cutouts w.r.t. the use of UIDs, allowing them to be preserved
or re-generated depending on an input parameter
- [x] Fix singlestate cutout extraction when memlets access struct
members.
---
 dace/sdfg/analysis/cutout.py | 56 ++++++++++++++++++++++++++++++------
 dace/sdfg/nodes.py           | 10 +++++++
 dace/sdfg/sdfg.py            | 10 +++++++
 3 files changed, 67 insertions(+), 9 deletions(-)

diff --git a/dace/sdfg/analysis/cutout.py b/dace/sdfg/analysis/cutout.py
index 5d2eae7c6f..ec95157989 100644
--- a/dace/sdfg/analysis/cutout.py
+++ b/dace/sdfg/analysis/cutout.py
@@ -118,7 +118,7 @@ def from_json(cls, json_obj, context=None):
     def from_transformation(
         cls, sdfg: SDFG, transformation: Union[PatternTransformation, SubgraphTransformation],
         make_side_effects_global = True, use_alibi_nodes: bool = True, reduce_input_config = True,
-        symbols_map: Optional[Dict[str, Any]] = None
+        symbols_map: Optional[Dict[str, Any]] = None, preserve_guids: bool = False
     ) -> Union['SDFGCutout', SDFG]:
         """
         Create a cutout from a transformation's set of affected graph elements.
@@ -130,6 +130,9 @@ def from_transformation(
         :param reduce_input_config: Whether to reduce the input configuration where possible in singlestate cutouts.
         :param symbols_map: A mapping of symbols to values to use for the cutout. Optional, only used when reducing the
                             input configuration.
+        :param preserve_guids: If True, ensures that the GUIDs of graph elements contained in the cutout remain
+                               identical to the ones in their original graph. If False, new GUIDs will be generated.
+                               False by default.
         :return: The cutout.
         """
         affected_nodes = _transformation_determine_affected_nodes(sdfg, transformation)
@@ -150,11 +153,12 @@ def from_transformation(
                 state = target_sdfg.node(transformation.state_id)
             cutout = cls.singlestate_cutout(state, *affected_nodes, make_side_effects_global=make_side_effects_global,
                                             use_alibi_nodes=use_alibi_nodes, reduce_input_config=reduce_input_config,
-                                            symbols_map=symbols_map)
+                                            symbols_map=symbols_map, preserve_guids=preserve_guids)
             cutout.translate_transformation_into(transformation)
             return cutout
         elif isinstance(transformation, MultiStateTransformation):
-            cutout = cls.multistate_cutout(*affected_nodes, make_side_effects_global=make_side_effects_global)
+            cutout = cls.multistate_cutout(*affected_nodes, make_side_effects_global=make_side_effects_global,
+                                           preserve_guids=preserve_guids)
             # If the cutout is an SDFG, there's no need to translate the transformation.
             if isinstance(cutout, SDFGCutout):
                 cutout.translate_transformation_into(transformation)
@@ -169,14 +173,15 @@ def singlestate_cutout(cls,
                            make_side_effects_global: bool = True,
                            use_alibi_nodes: bool = True,
                            reduce_input_config: bool = False,
-                           symbols_map: Optional[Dict[str, Any]] = None) -> 'SDFGCutout':
+                           symbols_map: Optional[Dict[str, Any]] = None,
+                           preserve_guids: bool = False) -> 'SDFGCutout':
         """
         Cut out a subgraph of a state from an SDFG to run separately for localized testing or optimization.
         The subgraph defined by the list of nodes will be extended to include access nodes of data containers necessary
         to run the graph separately. In addition, all transient data containers that may contain data when the cutout is
         executed are made global, as well as any transient data containers which are written to inside the cutout but
         may be read after the cutout.
-        
+
         :param state: The SDFG state in which the subgraph resides.
         :param nodes: The nodes in the subgraph to cut out.
         :param make_copy: If True, deep-copies every SDFG element in the copy. Otherwise, original references are kept.
@@ -188,17 +193,29 @@ def singlestate_cutout(cls,
         :param reduce_input_config: Whether to reduce the input configuration where possible in singlestate cutouts.
         :param symbols_map: A mapping of symbols to values to use for the cutout. Optional, only used when reducing the
                             input configuration.
+        :param preserve_guids: If True, ensures that the GUIDs of graph elements contained in the cutout remain
+                               identical to the ones in their original graph. If False, new GUIDs will be generated.
+                               False by default - if make_copy is False, this has no effect by extension.
         :return: The created SDFGCutout.
         """
         if reduce_input_config:
             nodes = _reduce_in_configuration(state, nodes, use_alibi_nodes, symbols_map)
-        create_element = copy.deepcopy if make_copy else (lambda x: x)
+
+        def clone_f(x: Union[Memlet, InterstateEdge, nd.Node, ControlFlowBlock]):
+            ret = copy.deepcopy(x)
+            if preserve_guids:
+                ret.guid = x.guid
+            return ret
+
+        create_element = clone_f if make_copy else (lambda x: x)
         sdfg = state.parent
         subgraph: StateSubgraphView = StateSubgraphView(state, nodes)
         subgraph = _extend_subgraph_with_access_nodes(state, subgraph, use_alibi_nodes)
 
         # Make a new SDFG with the included constants, used symbols, and data containers.
         cutout = SDFGCutout(sdfg.name + '_cutout', sdfg.constants_prop)
+        if preserve_guids:
+            cutout.guid = sdfg.guid
         cutout._base_sdfg = sdfg
         defined_syms = subgraph.defined_symbols()
         freesyms = subgraph.free_symbols
@@ -213,11 +230,24 @@ def singlestate_cutout(cls,
             memlet = edge.data
             if memlet.data in cutout.arrays:
                 continue
-            new_desc = sdfg.arrays[memlet.data].clone()
-            cutout.add_datadesc(memlet.data, new_desc)
+            dataname = memlet.data
+            if '.' in dataname:
+                # This is an access to a struct memeber, which typically happens for the memlets between an access node
+                # pointing to a struct (or view thereof), and a view pointing to the member. Assert that this is indeed
+                # the case (i.e., only one '.' is found in the name of the data being accessed), and if so, clone the
+                # struct (or struct view) data descriptor instad.
+                parts = dataname.split('.')
+                if len(parts) == 2:
+                    dataname = parts[0]
+                else:
+                    raise RuntimeError('Attempting to add invalid multi-nested data ' + memlet.data + ' to a cutout')
+            new_desc = sdfg.arrays[dataname].clone()
+            cutout.add_datadesc(dataname, new_desc)
 
         # Add a single state with the extended subgraph
         new_state = cutout.add_state(state.label, is_start_state=True)
+        if preserve_guids:
+            new_state.guid = state.guid
         in_translation = dict()
         out_translation = dict()
         for e in sg_edges:
@@ -322,6 +352,7 @@ def singlestate_cutout(cls,
     def multistate_cutout(cls,
                           *states: SDFGState,
                           make_side_effects_global: bool = True,
+                          preserve_guids: bool = False,
                           override_start_block: Optional[ControlFlowBlock] = None) -> Union['SDFGCutout', SDFG]:
         """
         Cut out a multi-state subgraph from an SDFG to run separately for localized testing or optimization.
@@ -337,12 +368,19 @@ def multistate_cutout(cls,
         :param make_side_effects_global: If True, all transient data containers which are read inside the cutout but may
                                         be written to _before_ the cutout, or any data containers which are written to
                                         inside the cutout but may be read _after_ the cutout, are made global.
+        :param preserve_guids: If True, ensures that the GUIDs of graph elements contained in the cutout remain
+                               identical to the ones in their original graph. If False, new GUIDs will be generated.
+                               False by default - if make_copy is False, this has no effect by extension.
         :param override_start_block: If set, explicitly force a given control flow block to be the start block. If left
                                      None (default), the start block is automatically determined based on domination
                                      relationships in the original graph.
         :return: The created SDFGCutout or the original SDFG where no smaller cutout could be obtained.
         """
-        create_element = copy.deepcopy
+        def create_element(x: Union[ControlFlowBlock, InterstateEdge]) -> Union[ControlFlowBlock, InterstateEdge]:
+            ret = copy.deepcopy(x)
+            if preserve_guids:
+                ret.guid = x.guid
+            return ret
 
         # Check that all states are inside the same SDFG.
         sdfg = list(states)[0].parent
diff --git a/dace/sdfg/nodes.py b/dace/sdfg/nodes.py
index 4ae91d5ea0..d29b1a22e4 100644
--- a/dace/sdfg/nodes.py
+++ b/dace/sdfg/nodes.py
@@ -55,6 +55,16 @@ def __str__(self):
         else:
             return type(self).__name__
 
+    def __deepcopy__(self, memo):
+        cls = self.__class__
+        result = cls.__new__(cls)
+        memo[id(self)] = result
+        for k, v in self.__dict__.items():
+            if k == 'guid': # Skip ID
+                continue
+            setattr(result, k, dcpy(v, memo))
+        return result
+
     def validate(self, sdfg, state):
         pass
 
diff --git a/dace/sdfg/sdfg.py b/dace/sdfg/sdfg.py
index cb8a7d5c2d..19d2a47295 100644
--- a/dace/sdfg/sdfg.py
+++ b/dace/sdfg/sdfg.py
@@ -205,6 +205,16 @@ def __setattr__(self, name: str, value: Any) -> None:
             super().__setattr__('_uncond', None)
         return super().__setattr__(name, value)
 
+    def __deepcopy__(self, memo):
+        cls = self.__class__
+        result = cls.__new__(cls)
+        memo[id(self)] = result
+        for k, v in self.__dict__.items():
+            if k == 'guid': # Skip ID
+                continue
+            setattr(result, k, copy.deepcopy(v, memo))
+        return result
+
     @staticmethod
     def _convert_assignment(assignment) -> str:
         if isinstance(assignment, ast.AST):

From 64d76799bf4f27f128b5301d97aecb78b634df2f Mon Sep 17 00:00:00 2001
From: Tal Ben-Nun <tbennun@users.noreply.github.com>
Date: Mon, 4 Nov 2024 08:44:54 -0800
Subject: [PATCH 12/33] Various stability improvements and convenience APIs
 (#1724)

* Various minor code generation and runtime fixes
* Minor API improvements to CompiledSDFG, sdfg.view(), and subset
offsetting
* Minor memlet propagation fix
* Various simplify pass fixes that pertain to use of views, references,
and tasklets with side effects
* Symbolic support for shift and ternary expressions (fixes #1315)
* Pass permissiveness into transformations
---
 dace/cli/sdfgcc.py                            |   2 +-
 dace/cli/sdfv.py                              |   6 +-
 dace/codegen/compiled_sdfg.py                 |   5 +
 dace/codegen/compiler.py                      |   2 +-
 dace/codegen/cppunparse.py                    |   8 +-
 dace/codegen/tools/type_inference.py          |   2 +
 dace/dtypes.py                                |   2 +
 dace/memlet.py                                |   4 +-
 dace/properties.py                            |   2 +-
 dace/runtime/include/dace/stream.h            |   8 +-
 dace/sdfg/graph.py                            |   2 +-
 dace/sdfg/propagation.py                      |   6 +-
 dace/sdfg/sdfg.py                             |   9 +-
 dace/sdfg/utils.py                            |  67 ++++++++--
 dace/sdfg/validation.py                       |   4 +-
 dace/subsets.py                               |  26 ++--
 dace/symbolic.py                              | 117 ++++++++++++++----
 .../dataflow/redundant_array.py               |  10 ++
 .../transformation/dataflow/tasklet_fusion.py | 102 +++++++++++++--
 dace/transformation/helpers.py                |   3 +
 dace/transformation/interstate/loop_to_map.py |   5 +-
 .../interstate/multistate_inline.py           |   3 +
 .../transformation/interstate/sdfg_nesting.py |   3 +
 .../transformation/interstate/state_fusion.py |   9 ++
 .../passes/analysis/analysis.py               |  55 +++++++-
 .../transformation/passes/pattern_matching.py |   2 +
 .../transformation/passes/scalar_to_symbol.py |  25 ++--
 tests/transformations/tasklet_fusion_test.py  |  35 +++++-
 28 files changed, 440 insertions(+), 84 deletions(-)

diff --git a/dace/cli/sdfgcc.py b/dace/cli/sdfgcc.py
index 1df7604b4b..0d04950be7 100644
--- a/dace/cli/sdfgcc.py
+++ b/dace/cli/sdfgcc.py
@@ -48,7 +48,7 @@ def main():
         sdfg = SDFGOptimizer(sdfg).optimize()
 
     # Compile SDFG
-    sdfg.compile(outpath)
+    sdfg.compile(outpath, return_program_handle=False)
 
     # Copying header file to optional path
     if outpath is not None:
diff --git a/dace/cli/sdfv.py b/dace/cli/sdfv.py
index 2012debe82..d14059468f 100644
--- a/dace/cli/sdfv.py
+++ b/dace/cli/sdfv.py
@@ -43,7 +43,11 @@ def view(sdfg: dace.SDFG, filename: Optional[Union[str, int]] = None, verbose: b
         ):
             fd, filename = tempfile.mkstemp(suffix='.sdfg')
             sdfg.save(filename)
-            os.system(f'code {filename}')
+            if platform.system() == 'Darwin':
+                # Special case for MacOS
+                os.system(f'open {filename}')
+            else:
+                os.system(f'code {filename}')
             os.close(fd)
             return
 
diff --git a/dace/codegen/compiled_sdfg.py b/dace/codegen/compiled_sdfg.py
index 9bfcc439e0..332db028ae 100644
--- a/dace/codegen/compiled_sdfg.py
+++ b/dace/codegen/compiled_sdfg.py
@@ -518,6 +518,9 @@ def _construct_args(self, kwargs) -> Tuple[Tuple[Any], Tuple[Any]]:
                     # Otherwise, None values are passed as null pointers below
                 elif isinstance(arg, ctypes._Pointer):
                     pass
+                elif isinstance(arg, str):
+                    # Cast to bytes
+                    arglist[i] = ctypes.c_char_p(arg.encode('utf-8'))
                 else:
                     raise TypeError(f'Passing an object (type {type(arg).__name__}) to an array in argument "{a}"')
             elif is_array and not is_dtArray:
@@ -550,6 +553,8 @@ def _construct_args(self, kwargs) -> Tuple[Tuple[Any], Tuple[Any]]:
                     pass
                 elif isinstance(arg, float) and atype.dtype.type == np.float64:
                     pass
+                elif isinstance(arg, bool) and atype.dtype.type == np.bool_:
+                    pass
                 elif (isinstance(arg, str) or arg is None) and atype.dtype == dtypes.string:
                     if arg is None:
                         arglist[i] = ctypes.c_char_p(None)
diff --git a/dace/codegen/compiler.py b/dace/codegen/compiler.py
index 350e141606..236f832cac 100644
--- a/dace/codegen/compiler.py
+++ b/dace/codegen/compiler.py
@@ -213,7 +213,7 @@ def configure_and_compile(program_folder, program_name=None, output_stream=None)
         # Clean CMake directory and try once more
         if Config.get_bool('debugprint'):
             print('Cleaning CMake build folder and retrying...')
-        shutil.rmtree(build_folder)
+        shutil.rmtree(build_folder, ignore_errors=True)
         os.makedirs(build_folder)
         try:
             _run_liveoutput(cmake_command, shell=True, cwd=build_folder, output_stream=output_stream)
diff --git a/dace/codegen/cppunparse.py b/dace/codegen/cppunparse.py
index edeb5270ca..c375147930 100644
--- a/dace/codegen/cppunparse.py
+++ b/dace/codegen/cppunparse.py
@@ -555,7 +555,11 @@ def _write_constant(self, value):
             if result.find("b'") >= 0:
                 self.write(result)
             else:
-                self.write(result.replace('\'', '\"'))
+                towrite = result
+                if result.startswith("'"):
+                    towrite = result[1:-1].replace('"', '\\"')
+                    towrite = f'"{towrite}"'
+                self.write(towrite)
 
     def _Constant(self, t):
         value = t.value
@@ -1187,6 +1191,8 @@ def py2cpp(code, expr_semicolon=True, defined_symbols=None):
         return cppunparse(ast.parse(symbolic.symstr(code, cpp_mode=True)),
                           expr_semicolon,
                           defined_symbols=defined_symbols)
+    elif isinstance(code, int):
+        return str(code)
     elif code.__class__.__name__ == 'function':
         try:
             code_str = inspect.getsource(code)
diff --git a/dace/codegen/tools/type_inference.py b/dace/codegen/tools/type_inference.py
index 8f8dd84151..26b369fa9d 100644
--- a/dace/codegen/tools/type_inference.py
+++ b/dace/codegen/tools/type_inference.py
@@ -375,6 +375,8 @@ def _Compare(t, symbols, inferred_symbols):
     for o, e in zip(t.ops, t.comparators):
         if o.__class__.__name__ not in cppunparse.CPPUnparser.cmpops:
             continue
+        if isinstance(e, ast.Constant) and e.value is None:
+            continue
         inf_type = _dispatch(e, symbols, inferred_symbols)
         if isinstance(inf_type, dtypes.vector):
             # Make sure all occuring vectors are of same size
diff --git a/dace/dtypes.py b/dace/dtypes.py
index a016ac60e2..d0c6f23e03 100644
--- a/dace/dtypes.py
+++ b/dace/dtypes.py
@@ -404,6 +404,8 @@ def __init__(self, wrapped_type, typename=None):
             wrapped_type = numpy.bool_
         elif getattr(wrapped_type, '__name__', '') == 'bool_' and typename is None:
             typename = 'bool'
+        elif wrapped_type is type(None):
+            wrapped_type = None
 
         self.type = wrapped_type  # Type in Python
         self.ctype = _CTYPES[wrapped_type]  # Type in C
diff --git a/dace/memlet.py b/dace/memlet.py
index f78da3a6b7..85bd0a348d 100644
--- a/dace/memlet.py
+++ b/dace/memlet.py
@@ -555,9 +555,9 @@ def used_symbols(self, all_symbols: bool, edge=None) -> Set[str]:
             from dace.sdfg import nodes
             if isinstance(edge.dst, nodes.CodeNode) or isinstance(edge.src, nodes.CodeNode):
                 view_edge = True
-            elif edge.dst_conn == 'views' and isinstance(edge.dst, nodes.AccessNode):
+            elif edge.dst_conn and isinstance(edge.dst, nodes.AccessNode):
                 view_edge = True
-            elif edge.src_conn == 'views' and isinstance(edge.src, nodes.AccessNode):
+            elif edge.src_conn and isinstance(edge.src, nodes.AccessNode):
                 view_edge = True
 
         if not view_edge:
diff --git a/dace/properties.py b/dace/properties.py
index 09439ce4f8..82be72f9fd 100644
--- a/dace/properties.py
+++ b/dace/properties.py
@@ -329,7 +329,7 @@ def initialize_properties(obj, *args, **kwargs):
         for name, prop in own_properties.items():
             # Only assign our own properties, so we don't overwrite what's been
             # set by the base class
-            if hasattr(obj, name):
+            if hasattr(obj, '_' + name):
                 raise PropertyError("Property {} already assigned in {}".format(name, type(obj).__name__))
             if not prop.indirected:
                 if prop.allow_none or prop.default is not None:
diff --git a/dace/runtime/include/dace/stream.h b/dace/runtime/include/dace/stream.h
index 255e16ec2b..1f8134fae6 100644
--- a/dace/runtime/include/dace/stream.h
+++ b/dace/runtime/include/dace/stream.h
@@ -338,7 +338,7 @@ namespace dace {
 
     template <int CHUNKSIZE>
     struct Consume {
-        template <template <typename, bool> typename StreamT, typename T, bool ALIGNED,
+        template <template <typename, bool> class StreamT, typename T, bool ALIGNED,
                   typename Functor>
         static void consume(StreamT<T, ALIGNED>& stream, unsigned num_threads,
                             Functor&& contents) {
@@ -359,7 +359,7 @@ namespace dace {
             for (auto& t : threads) t.join();
         }
 
-        template <template <typename, bool> typename StreamT, typename T, bool ALIGNED,
+        template <template <typename, bool> class StreamT, typename T, bool ALIGNED,
                   typename CondFunctor, typename Functor>
         static void consume_cond(StreamT<T, ALIGNED>& stream, unsigned num_threads,
                                  CondFunctor&& quiescence, Functor&& contents) {
@@ -384,7 +384,7 @@ namespace dace {
     // Specialization for consumption of 1 element
     template<>
     struct Consume<1> {
-        template <template <typename, bool> typename StreamT, typename T, bool ALIGNED,
+        template <template <typename, bool> class StreamT, typename T, bool ALIGNED,
                   typename Functor>
         static void consume(StreamT<T, ALIGNED>& stream, unsigned num_threads,
                             Functor&& contents) {
@@ -404,7 +404,7 @@ namespace dace {
             for (auto& t : threads) t.join();
         }
 
-        template <template <typename, bool> typename StreamT, typename T, bool ALIGNED,
+        template <template <typename, bool> class StreamT, typename T, bool ALIGNED,
                   typename CondFunctor, typename Functor>
         static void consume_cond(StreamT<T, ALIGNED>& stream, unsigned num_threads,
                                  CondFunctor&& quiescence, Functor&& contents) {
diff --git a/dace/sdfg/graph.py b/dace/sdfg/graph.py
index 5ec4bbb029..b8dcfd4e8f 100644
--- a/dace/sdfg/graph.py
+++ b/dace/sdfg/graph.py
@@ -409,7 +409,7 @@ def all_simple_paths(self,
             for path in map(nx.utils.pairwise, nx.all_simple_paths(self._nx, source_node, dest_node)):
                 yield [Edge(e[0], e[1], self._nx.edges[e]['data']) for e in path]
         else:
-            return nx.all_simple_paths(self._nx, source_node, dest_node)
+            yield from nx.all_simple_paths(self._nx, source_node, dest_node)
 
     def all_nodes_between(self, begin: NodeT, end: NodeT) -> Sequence[NodeT]:
         """Finds all nodes between begin and end. Returns None if there is any
diff --git a/dace/sdfg/propagation.py b/dace/sdfg/propagation.py
index a24db0c72b..f048389421 100644
--- a/dace/sdfg/propagation.py
+++ b/dace/sdfg/propagation.py
@@ -377,7 +377,7 @@ def can_be_applied(self, dim_exprs, variable_context, node_range, orig_edges, di
                 matches = rngelem.match(cst)
                 if matches is None or len(matches) != 1:
                     return False
-                if not matches[cst].is_constant():
+                if matches[cst].free_symbols:
                     return False
 
         else:  # Single element case
@@ -386,7 +386,7 @@ def can_be_applied(self, dim_exprs, variable_context, node_range, orig_edges, di
                 matches = dexpr.match(cst)
                 if matches is None or len(matches) != 1:
                     return False
-                if not matches[cst].is_constant():
+                if matches[cst].free_symbols:
                     return False
 
         return True
@@ -1296,6 +1296,8 @@ def align_memlet(state, e: gr.MultiConnectorEdge[Memlet], dst: bool) -> Memlet:
     # Fix memlet fields
     result.data = node.data
     result.subset = e.data.other_subset
+    if result.subset is None:
+        result.subset = subsets.Range.from_array(state.sdfg.arrays[result.data])
     result.other_subset = e.data.subset
     result._is_data_src = not is_src
     return result
diff --git a/dace/sdfg/sdfg.py b/dace/sdfg/sdfg.py
index 19d2a47295..3be268e44d 100644
--- a/dace/sdfg/sdfg.py
+++ b/dace/sdfg/sdfg.py
@@ -2266,14 +2266,16 @@ def is_loaded(self) -> bool:
         dll = cs.ReloadableDLL(binary_filename, self.name)
         return dll.is_loaded()
 
-    def compile(self, output_file=None, validate=True) -> 'CompiledSDFG':
+    def compile(self, output_file=None, validate=True,
+                return_program_handle=True) -> 'CompiledSDFG':
         """ Compiles a runnable binary from this SDFG.
 
             :param output_file: If not None, copies the output library file to
                                 the specified path.
             :param validate: If True, validates the SDFG prior to generating
                              code.
-            :return: A callable CompiledSDFG object.
+            :param return_program_handle: If False, does not load the generated library.
+            :return: A callable CompiledSDFG object, or None if ``return_program_handle=False``.
         """
 
         # Importing these outside creates an import loop
@@ -2336,7 +2338,8 @@ def compile(self, output_file=None, validate=True) -> 'CompiledSDFG':
             shutil.copyfile(shared_library, output_file)
 
         # Get the function handle
-        return compiler.get_program_handle(shared_library, sdfg)
+        if return_program_handle:
+            return compiler.get_program_handle(shared_library, sdfg)
 
     def argument_typecheck(self, args, kwargs, types_only=False):
         """ Checks if arguments and keyword arguments match the SDFG
diff --git a/dace/sdfg/utils.py b/dace/sdfg/utils.py
index 5b9ce1a431..623a82c5bf 100644
--- a/dace/sdfg/utils.py
+++ b/dace/sdfg/utils.py
@@ -629,9 +629,13 @@ def remove_edge_and_dangling_path(state: SDFGState, edge: MultiConnectorEdge):
         e = curedge.edge
         state.remove_edge(e)
         if inwards:
-            neighbors = [] if not e.src_conn else [neighbor for neighbor in state.out_edges_by_connector(e.src, e.src_conn)]
+            neighbors = [] if not e.src_conn else [
+                neighbor for neighbor in state.out_edges_by_connector(e.src, e.src_conn)
+            ]
         else:
-            neighbors = [] if not e.dst_conn else [neighbor for neighbor in state.in_edges_by_connector(e.dst, e.dst_conn)]
+            neighbors = [] if not e.dst_conn else [
+                neighbor for neighbor in state.in_edges_by_connector(e.dst, e.dst_conn)
+            ]
         if len(neighbors) > 0:  # There are still edges connected, leave as-is
             break
 
@@ -796,6 +800,33 @@ def get_all_view_nodes(state: SDFGState, view: nd.AccessNode) -> List[nd.AccessN
     return result
 
 
+def get_all_view_edges(state: SDFGState, view: nd.AccessNode) -> List[gr.MultiConnectorEdge[mm.Memlet]]:
+    """
+    Given a view access node, returns a list of viewed access nodes as edges
+    if existent, else None
+    """
+    sdfg = state.parent
+    node = view
+    desc = sdfg.arrays[node.data]
+    result = []
+    while isinstance(desc, dt.View):
+        edge = get_view_edge(state, node)
+        if edge is None:
+            break
+        old_node = node
+        if edge.dst is view:
+            node = edge.src
+        else:
+            node = edge.dst
+        if node is old_node:
+            break
+        if not isinstance(node, nd.AccessNode):
+            break
+        desc = sdfg.arrays[node.data]
+        result.append(edge)
+    return result
+
+
 def get_view_edge(state: SDFGState, view: nd.AccessNode) -> gr.MultiConnectorEdge[mm.Memlet]:
     """
     Given a view access node, returns the
@@ -818,8 +849,18 @@ def get_view_edge(state: SDFGState, view: nd.AccessNode) -> gr.MultiConnectorEdg
     # If there is one edge (in/out) that leads (via memlet path) to an access
     # node, and the other side (out/in) has a different number of edges.
     if len(in_edges) == 1 and len(out_edges) != 1:
+        # If the edge is not leading to an access node, fail
+        mpath = state.memlet_path(in_edges[0])
+        if not isinstance(mpath[0].src, nd.AccessNode):
+            return None
+
         return in_edges[0]
     if len(out_edges) == 1 and len(in_edges) != 1:
+        # If the edge is not leading to an access node, fail
+        mpath = state.memlet_path(out_edges[0])
+        if not isinstance(mpath[-1].dst, nd.AccessNode):
+            return None
+
         return out_edges[0]
     if len(out_edges) == len(in_edges) and len(out_edges) != 1:
         return None
@@ -843,7 +884,7 @@ def get_view_edge(state: SDFGState, view: nd.AccessNode) -> gr.MultiConnectorEdg
         return out_edge
     if not src_is_data and not dst_is_data:
         return None
-    
+
     # Check if there is a 'views' connector
     if in_edge.dst_conn and in_edge.dst_conn == 'views':
         return in_edge
@@ -1227,8 +1268,8 @@ def fuse_states(sdfg: SDFG, permissive: bool = False, progress: bool = None) ->
                         progress = True
                         pbar = tqdm(total=fusible_states, desc='Fusing states', initial=counter)
 
-                    if (u in skip_nodes or v in skip_nodes or not isinstance(v, SDFGState) or
-                        not isinstance(u, SDFGState)):
+                    if (u in skip_nodes or v in skip_nodes or not isinstance(v, SDFGState)
+                            or not isinstance(u, SDFGState)):
                         continue
                     candidate = {StateFusion.first_state: u, StateFusion.second_state: v}
                     sf = StateFusion()
@@ -1252,8 +1293,7 @@ def inline_loop_blocks(sdfg: SDFG, permissive: bool = False, progress: bool = No
     blocks = [n for n, _ in sdfg.all_nodes_recursive() if isinstance(n, LoopRegion)]
     count = 0
 
-    for _block in optional_progressbar(reversed(blocks), title='Inlining Loops',
-                                       n=len(blocks), progress=progress):
+    for _block in optional_progressbar(reversed(blocks), title='Inlining Loops', n=len(blocks), progress=progress):
         block: LoopRegion = _block
         if block.inline()[0]:
             count += 1
@@ -1265,20 +1305,25 @@ def inline_control_flow_regions(sdfg: SDFG, permissive: bool = False, progress:
     blocks = [n for n, _ in sdfg.all_nodes_recursive() if isinstance(n, ControlFlowRegion)]
     count = 0
 
-    for _block in optional_progressbar(reversed(blocks), title='Inlining control flow regions',
-                                       n=len(blocks), progress=progress):
+    for _block in optional_progressbar(reversed(blocks),
+                                       title='Inlining control flow regions',
+                                       n=len(blocks),
+                                       progress=progress):
         block: ControlFlowRegion = _block
         if block.inline()[0]:
             count += 1
 
     return count
 
+
 def inline_conditional_blocks(sdfg: SDFG, permissive: bool = False, progress: bool = None) -> int:
     blocks = [n for n, _ in sdfg.all_nodes_recursive() if isinstance(n, ConditionalBlock)]
     count = 0
 
-    for _block in optional_progressbar(reversed(blocks), title='Inlining conditional blocks',
-                                       n=len(blocks), progress=progress):
+    for _block in optional_progressbar(reversed(blocks),
+                                       title='Inlining conditional blocks',
+                                       n=len(blocks),
+                                       progress=progress):
         block: ConditionalBlock = _block
         if block.inline()[0]:
             count += 1
diff --git a/dace/sdfg/validation.py b/dace/sdfg/validation.py
index 2df9e17445..0b1d946798 100644
--- a/dace/sdfg/validation.py
+++ b/dace/sdfg/validation.py
@@ -836,7 +836,7 @@ def validate_state(state: 'dace.sdfg.SDFGState',
             dst_expr = (e.data.dst_subset.num_elements() * sdfg.arrays[dst_node.data].veclen)
             if symbolic.inequal_symbols(src_expr, dst_expr):
                 error = InvalidSDFGEdgeError('Dimensionality mismatch between src/dst subsets', sdfg, state_id, eid)
-                # NOTE: Make an exception for Views
+                # NOTE: Make an exception for Views and reference sets
                 from dace.sdfg import utils
                 if (isinstance(sdfg.arrays[src_node.data], dt.View) and utils.get_view_edge(state, src_node) is e):
                     warnings.warn(error.message)
@@ -844,6 +844,8 @@ def validate_state(state: 'dace.sdfg.SDFGState',
                 if (isinstance(sdfg.arrays[dst_node.data], dt.View) and utils.get_view_edge(state, dst_node) is e):
                     warnings.warn(error.message)
                     continue
+                if e.dst_conn == 'set':
+                    continue
                 raise error
 
     if Config.get_bool('experimental.check_race_conditions'):
diff --git a/dace/subsets.py b/dace/subsets.py
index e7b6869678..0fa6fb536c 100644
--- a/dace/subsets.py
+++ b/dace/subsets.py
@@ -162,10 +162,10 @@ def covers_precise(self, other):
     def __repr__(self):
         return '%s (%s)' % (type(self).__name__, self.__str__())
 
-    def offset(self, other, negative, indices=None):
+    def offset(self, other, negative, indices=None, offset_end=True):
         raise NotImplementedError
 
-    def offset_new(self, other, negative, indices=None):
+    def offset_new(self, other, negative, indices=None, offset_end=True):
         raise NotImplementedError
 
     def at(self, i, strides):
@@ -229,6 +229,7 @@ def _tuple_to_symexpr(val):
 @dace.serialize.serializable
 class Range(Subset):
     """ Subset defined in terms of a fixed range. """
+
     def __init__(self, ranges):
         parsed_ranges = []
         parsed_tiles = []
@@ -402,7 +403,7 @@ def data_dims(self):
         return (sum(1 if (re - rb + 1) != 1 else 0 for rb, re, _ in self.ranges) + sum(1 if ts != 1 else 0
                                                                                        for ts in self.tile_sizes))
 
-    def offset(self, other, negative, indices=None):
+    def offset(self, other, negative, indices=None, offset_end=True):
         if not isinstance(other, Subset):
             if isinstance(other, (list, tuple)):
                 other = Indices(other)
@@ -414,9 +415,11 @@ def offset(self, other, negative, indices=None):
         off = other.min_element()
         for i in indices:
             rb, re, rs = self.ranges[i]
-            self.ranges[i] = (rb + mult * off[i], re + mult * off[i], rs)
+            if offset_end:
+                re = re + mult * off[i]
+            self.ranges[i] = (rb + mult * off[i], re, rs)
 
-    def offset_new(self, other, negative, indices=None):
+    def offset_new(self, other, negative, indices=None, offset_end=True):
         if not isinstance(other, Subset):
             if isinstance(other, (list, tuple)):
                 other = Indices(other)
@@ -426,8 +429,8 @@ def offset_new(self, other, negative, indices=None):
         if indices is None:
             indices = set(range(len(self.ranges)))
         off = other.min_element()
-        return Range([(self.ranges[i][0] + mult * off[i], self.ranges[i][1] + mult * off[i], self.ranges[i][2])
-                      for i in indices])
+        return Range([(self.ranges[i][0] + mult * off[i], self.ranges[i][1] if not offset_end else
+                       (self.ranges[i][1] + mult * off[i]), self.ranges[i][2]) for i in indices])
 
     def dims(self):
         return len(self.ranges)
@@ -848,9 +851,11 @@ def intersects(self, other: 'Range'):
 class Indices(Subset):
     """ A subset of one element representing a single index in an
         N-dimensional data descriptor. """
+
     def __init__(self, indices):
         if indices is None or len(indices) == 0:
-            raise TypeError('Expected an array of index expressions: got empty' ' array or None')
+            raise TypeError('Expected an array of index expressions: got empty'
+                            ' array or None')
         if isinstance(indices, str):
             raise TypeError("Expected collection of index expression: got str")
         elif isinstance(indices, symbolic.SymExpr):
@@ -860,6 +865,7 @@ def __init__(self, indices):
         self.tile_sizes = [1]
 
     def to_json(self):
+
         def a2s(obj):
             if isinstance(obj, symbolic.SymExpr):
                 return str(obj.expr)
@@ -919,7 +925,7 @@ def strides(self):
     def absolute_strides(self, global_shape):
         return [1] * len(self.indices)
 
-    def offset(self, other, negative, indices=None):
+    def offset(self, other, negative, indices=None, offset_end=True):
         if not isinstance(other, Subset):
             if isinstance(other, (list, tuple)):
                 other = Indices(other)
@@ -929,7 +935,7 @@ def offset(self, other, negative, indices=None):
         for i, off in enumerate(other.min_element()):
             self.indices[i] += mult * off
 
-    def offset_new(self, other, negative, indices=None):
+    def offset_new(self, other, negative, indices=None, offset_end=True):
         if not isinstance(other, Subset):
             if isinstance(other, (list, tuple)):
                 other = Indices(other)
diff --git a/dace/symbolic.py b/dace/symbolic.py
index 6218bbe715..9737080c52 100644
--- a/dace/symbolic.py
+++ b/dace/symbolic.py
@@ -23,7 +23,6 @@
 # below, we recreate it to be as in versions < 1.9.
 _sympy_clash = {k: v if v else getattr(sympy.abc, k) for k, v in sympy.abc._clash.items()}
 
-
 # SymPy 1.13 changes the behavior of `==` such that floats with different precisions
 # are always different.
 # For DaCe, mostly the comparison of value (ignoring precision) is relevant which
@@ -31,6 +30,7 @@
 # SymPy 1.12, so we fall back to `==` in that case (which ignores precision in those versions).
 # For convenience, we provide this functionality in our own SymPy layer.
 if packaging_version.Version(sympy.__version__) < packaging_version.Version("1.12"):
+
     def equal_valued(x, y):
         return x == y
 else:
@@ -584,6 +584,8 @@ def eval(cls, x, y):
         """
         if x.is_Number and y.is_Number:
             return x // y
+        if y.is_Number and y == 1:
+            return x
 
     def _eval_is_integer(self):
         return True
@@ -658,31 +660,79 @@ def eval(cls, x, y, z):
         if x.is_Boolean:
             return (y if x else z)
 
+    def _eval_is_real(self):
+        if self.args[1].is_real is True and self.args[2].is_real is True:
+            return True
+        if self.args[1].is_real is False and self.args[2].is_real is False:
+            return False
 
-class BitwiseAnd(sympy.Function):
-    pass
+    def _eval_is_nonnegative(self):
+        if self.args[1].is_nonnegative is True and self.args[2].is_nonnegative is True:
+            return True
+        if self.args[1].is_nonnegative is False and self.args[2].is_nonnegative is False:
+            return False
 
+    def _eval_is_positive(self):
+        if self.args[1].is_positive is True and self.args[2].is_positive is True:
+            return True
+        if self.args[1].is_positive is False and self.args[2].is_positive is False:
+            return False
 
-class BitwiseOr(sympy.Function):
-    pass
+    def _eval_is_integer(self):
+        if self.args[1].is_integer is True and self.args[2].is_integer is True:
+            return True
+        if self.args[1].is_integer is False and self.args[2].is_integer is False:
+            return False
 
 
-class BitwiseXor(sympy.Function):
+class bitwise_and(sympy.Function):
     pass
 
 
-class BitwiseNot(sympy.Function):
+class bitwise_or(sympy.Function):
     pass
 
 
-class LeftShift(sympy.Function):
+class bitwise_xor(sympy.Function):
     pass
 
 
-class RightShift(sympy.Function):
+class bitwise_invert(sympy.Function):
     pass
 
 
+class left_shift(sympy.Function):
+
+    @classmethod
+    def eval(cls, x, y):
+        """
+        Evaluates a left shift.
+
+        :param x: Value to shift.
+        :param y: Value to shift by.
+        :return: Return value (literal or symbolic).
+        """
+        if x.is_Number and y.is_Number:
+            return x << y
+        return x * (2**y)
+
+
+class right_shift(sympy.Function):
+
+    @classmethod
+    def eval(cls, x, y):
+        """
+        Evaluates a right shift.
+
+        :param x: Value to shift.
+        :param y: Value to shift by.
+        :return: Return value (literal or symbolic).
+        """
+        if x.is_Number and y.is_Number:
+            return x >> y
+        return int_floor(x, (2**y))
+
+
 class ROUND(sympy.Function):
 
     @classmethod
@@ -724,7 +774,7 @@ def free_symbols(self):
 
     def __str__(self):
         return f'{self.args[0]}.{self.args[1]}'
-    
+
     def _subs(self, *args, **kwargs):
         return Attr(self.args[0].subs(*args, **kwargs), self.args[1].subs(*args, **kwargs))
 
@@ -951,12 +1001,12 @@ class PythonOpToSympyConverter(ast.NodeTransformer):
     }
 
     _ast_to_sympy_functions = {
-        ast.BitAnd: 'BitwiseAnd',
-        ast.BitOr: 'BitwiseOr',
-        ast.BitXor: 'BitwiseXor',
-        ast.Invert: 'BitwiseNot',
-        ast.LShift: 'LeftShift',
-        ast.RShift: 'RightShift',
+        ast.BitAnd: 'bitwise_and',
+        ast.BitOr: 'bitwise_or',
+        ast.BitXor: 'bitwise_xor',
+        ast.Invert: 'bitwise_invert',
+        ast.LShift: 'left_shift',
+        ast.RShift: 'right_shift',
         ast.FloorDiv: 'int_floor',
     }
 
@@ -970,18 +1020,35 @@ def visit_UnaryOp(self, node):
                                           node)
             new_node = ast.Call(func=func_node, args=[self.visit(node.operand)], keywords=[])
             return ast.copy_location(new_node, node)
+
+        # Convert arithmetic expressions of the form "-(a == b)" to ternary operators
+        node.operand = self._convert_boolop_to_ifexpr(node.operand)
+
         return self.generic_visit(node)
 
     def visit_BinOp(self, node):
+        # Convert arithmetic expressions of the form "a + (b == c)" to ternary operators
+        node.left = self._convert_boolop_to_ifexpr(node.left)
+        node.right = self._convert_boolop_to_ifexpr(node.right)
+
         if type(node.op) in self._ast_to_sympy_functions:
             func_node = ast.copy_location(ast.Name(id=self._ast_to_sympy_functions[type(node.op)], ctx=ast.Load()),
                                           node)
+
             new_node = ast.Call(func=func_node,
                                 args=[self.visit(value) for value in (node.left, node.right)],
                                 keywords=[])
             return ast.copy_location(new_node, node)
         return self.generic_visit(node)
 
+    def _convert_boolop_to_ifexpr(self, node: ast.AST):
+        if isinstance(node, ast.Compare):
+            return ast.copy_location(
+                ast.Call(func=ast.Name(id='IfExpr', ctx=ast.Load),
+                         args=[node, ast.Constant(value=1), ast.Constant(value=0)],
+                         keywords=[]), node)
+        return node
+
     def visit_BoolOp(self, node):
         func_node = ast.copy_location(ast.Name(id=type(node.op).__name__, ctx=ast.Load()), node)
 
@@ -1076,12 +1143,18 @@ def pystr_to_symbolic(expr, symbol_map=None, simplify=None) -> sympy.Basic:
         'arg': sympy.Symbol('arg'),
         'Is': Is,
         'IsNot': IsNot,
-        'BitwiseAnd': BitwiseAnd,
-        'BitwiseOr': BitwiseOr,
-        'BitwiseXor': BitwiseXor,
-        'BitwiseNot': BitwiseNot,
-        'LeftShift': LeftShift,
-        'RightShift': RightShift,
+        'BitwiseAnd': bitwise_and,
+        'BitwiseOr': bitwise_or,
+        'BitwiseXor': bitwise_xor,
+        'BitwiseNot': bitwise_invert,
+        'bitwise_and': bitwise_and,
+        'bitwise_or': bitwise_or,
+        'bitwise_xor': bitwise_xor,
+        'bitwise_invert': bitwise_invert,
+        'LeftShift': left_shift,
+        'left_shift': left_shift,
+        'RightShift': right_shift,
+        'right_shift': right_shift,
         'int_floor': int_floor,
         'int_ceil': int_ceil,
         'IfExpr': IfExpr,
diff --git a/dace/transformation/dataflow/redundant_array.py b/dace/transformation/dataflow/redundant_array.py
index 7b241ff9cd..5e5072ff32 100644
--- a/dace/transformation/dataflow/redundant_array.py
+++ b/dace/transformation/dataflow/redundant_array.py
@@ -196,6 +196,10 @@ def can_be_applied(self, graph: SDFGState, expr_index, sdfg, permissive=False):
         if not in_desc.transient:
             return False
 
+        # Skip structure views
+        if isinstance(in_desc, data.StructureView) or isinstance(out_desc, data.StructureView):
+            return False
+
         # 1. Get edge e1 and extract subsets for arrays A and B
         e1 = graph.edges_between(in_array, out_array)[0]
         try:
@@ -705,6 +709,10 @@ def can_be_applied(self, graph, expr_index, sdfg, permissive=False):
         if not out_desc.transient:
             return False
 
+        # Skip structure views
+        if isinstance(in_desc, data.StructureView) or isinstance(out_desc, data.StructureView):
+            return False
+
         # 1. Get edge e1 and extract/validate subsets for arrays A and B
         e1 = graph.edges_between(in_array, out_array)[0]
         try:
@@ -1528,6 +1536,8 @@ def can_be_applied(self, state: SDFGState, _: int, sdfg: SDFG, permissive=False)
         # Ensure view
         if not isinstance(desc, data.View):
             return False
+        if isinstance(desc, data.StructureView):
+            return False
 
         # Get viewed node and non-viewed edges
         view_edge = sdutil.get_view_edge(state, self.view)
diff --git a/dace/transformation/dataflow/tasklet_fusion.py b/dace/transformation/dataflow/tasklet_fusion.py
index 29bb014263..183b98c402 100644
--- a/dace/transformation/dataflow/tasklet_fusion.py
+++ b/dace/transformation/dataflow/tasklet_fusion.py
@@ -3,20 +3,21 @@
 
 import ast
 import re
-from typing import Any, Dict
+from typing import Any, Dict, Optional, Set
 
 import astunparse
 import dace
 from dace.dtypes import Language
+from dace.properties import make_properties, Property
 from dace.sdfg import nodes
 from dace.sdfg import utils as sdutil
 from dace.transformation import transformation as pm
-from dace.transformation import helpers as thelpers
 
 
 class PythonConnectorRenamer(ast.NodeTransformer):
     """ Renames connector names in Tasklet code.
     """
+
     def __init__(self, repl_dict: Dict[str, str]) -> None:
         """ Initializes AST transformer.
         
@@ -32,6 +33,7 @@ def visit_Name(self, node: ast.Name) -> Any:
 
 
 class CPPConnectorRenamer():
+
     def __init__(self, repl_dict: Dict[str, str]) -> None:
         self.repl_dict = repl_dict
 
@@ -43,6 +45,7 @@ def rename(self, code: str) -> str:
 
 
 class PythonInliner(ast.NodeTransformer):
+
     def __init__(self, target_id, target_ast):
         self.target_id = target_id
         self.target_ast = target_ast
@@ -55,6 +58,7 @@ def visit_Name(self, node: ast.AST):
 
 
 class CPPInliner():
+
     def __init__(self, inline_target, inline_val):
         self.inline_target = inline_target
         self.inline_val = inline_val
@@ -63,6 +67,7 @@ def inline(self, code: str):
         return re.sub(r'\b%s\b' % re.escape(self.inline_target), '(' + self.inline_val + ')', code)
 
 
+@make_properties
 class TaskletFusion(pm.SingleStateTransformation):
     """
     Fuses two connected Tasklets.
@@ -139,6 +144,11 @@ class TaskletFusion(pm.SingleStateTransformation):
     data = pm.PatternNode(nodes.AccessNode)
     t2 = pm.PatternNode(nodes.Tasklet)
 
+    new_name = Property(dtype=str,
+                        default=None,
+                        allow_none=True,
+                        desc='New name to give tasklet. If None, fuses tasklet names')
+
     @classmethod
     def expressions(cls):
         return [sdutil.node_path_graph(cls.t1, cls.data, cls.t2), sdutil.node_path_graph(cls.t1, cls.t2)]
@@ -157,9 +167,14 @@ def can_be_applied(self, graph: dace.SDFGState, expr_index: int, sdfg: dace.SDFG
             return False
 
         # The first Tasklet must not be used anywhere else. If the Tasklet leads into an AccessNode, that AccessNode in
-        # turn can not be used anywhere else.
+        # turn cannot be used anywhere else.
         if graph.out_degree(t1) != 1 or (data is not None and graph.out_degree(data) != 1):
             return False
+        if data is not None:
+            access_node_count = sum(1 for s in sdfg.nodes() for n in s.data_nodes() if n.data == data.data)
+            access_node_count += sum(1 for e in sdfg.edges() if data.data in e.data.free_symbols)
+            if access_node_count > 1:
+                return False
 
         # Try to parse the code to check that there is not more than one assignment.
         try:
@@ -186,6 +201,8 @@ def apply(self, graph: dace.SDFGState, sdfg: dace.SDFG):
 
         # Remove the connector from the second Tasklet.
         inputs = {k: v for k, v in t2.in_connectors.items() if k != t2_in_edge.dst_conn}
+        all_conns = set(inputs.keys()) | set(t2.out_connectors)
+        all_conns_with_inputs = all_conns | set(t1.in_connectors)
 
         # Copy the first Tasklet's in connectors.
         repldict = {}
@@ -195,7 +212,15 @@ def apply(self, graph: dace.SDFGState, sdfg: dace.SDFG):
                 continue
 
             # Check if there is a conflict.
-            if in_edge.dst_conn in inputs:
+            if in_edge.dst_conn in all_conns:
+
+                # Check for conflicts with the second tasklet's output connectors
+                if in_edge.dst_conn in t2.out_connectors:
+                    in_edge.dst_conn = dace.data.find_new_name(in_edge.dst_conn, all_conns_with_inputs)
+                    repldict[old_value] = in_edge.dst_conn
+                    inputs[in_edge.dst_conn] = t1.in_connectors[old_value]
+                    continue
+
                 # Conflicts are ok if the Memlets are the same.
                 conflict_edges = list(graph.in_edges_by_connector(t2, in_edge.dst_conn))
                 t2edge = None
@@ -208,7 +233,7 @@ def apply(self, graph: dace.SDFGState, sdfg: dace.SDFG):
                     t2edge = conflict_edges[0]
                 if t2edge is not None and (in_edge.data != t2edge.data or in_edge.data.data != t2edge.data.data
                                            or in_edge.data is None or in_edge.data.data is None):
-                    in_edge.dst_conn = dace.data.find_new_name(in_edge.dst_conn, set(inputs))
+                    in_edge.dst_conn = dace.data.find_new_name(in_edge.dst_conn, all_conns_with_inputs)
                     repldict[old_value] = in_edge.dst_conn
                 else:
                     # If the Memlets are the same, rename the connector on the first Tasklet, such that we only have
@@ -243,10 +268,25 @@ def apply(self, graph: dace.SDFGState, sdfg: dace.SDFG):
             if rhs:
                 new_code_str = CPPInliner(t2_in_edge.dst_conn, rhs).inline(t2.code.as_string)
         else:
-            return
+            raise ValueError(f'Cannot inline tasklet with language {t1.language}')
 
-        new_tasklet = graph.add_tasklet(t1.label + '_fused_' + t2.label, inputs, t2.out_connectors, new_code_str,
-                                        t1.language)
+        if self.new_name:
+            new_name = self.new_name
+        else:
+            new_name = t1.label + '_fused_' + t2.label
+
+        new_tasklet = graph.add_tasklet(new_name,
+                                        inputs,
+                                        t2.out_connectors,
+                                        new_code_str,
+                                        t1.language,
+                                        state_fields=t1.state_fields + t2.state_fields,
+                                        code_global=t1.code_global.code + t2.code_global.code,
+                                        code_init=t1.code_init.code + t2.code_init.code,
+                                        code_exit=t1.code_exit.code + t2.code_exit.code,
+                                        location=_merge_dicts(t1.location, t2.location),
+                                        side_effects=t1.side_effects or t2.side_effects,
+                                        debuginfo=_merge_debuginfo(t1.debuginfo, t2.debuginfo))
 
         for in_edge in graph.in_edges(t1):
             if in_edge.src_conn is None and isinstance(in_edge.src, dace.nodes.EntryNode):
@@ -269,3 +309,49 @@ def apply(self, graph: dace.SDFGState, sdfg: dace.SDFG):
             graph.remove_node(data)
 
         graph.remove_node(t2)
+
+
+def _merge_dicts(a: Optional[Dict[Any, Any]], b: Optional[Dict[Any, Any]]):
+    if a is None and b is not None:
+        return b
+    if b is None and a is not None:
+        return a
+    result = dict()
+    result.update(a)
+    result.update(b)
+    return result
+
+
+def _merge_sets(a: Optional[Set[Any]], b: Optional[Set[Any]]):
+    if a is None and b is not None:
+        return b
+    if b is None and a is not None:
+        return a
+    result = set()
+    result.update(a)
+    result.update(b)
+    return result
+
+
+def _merge_debuginfo(a: Optional[dace.DebugInfo], b: Optional[dace.DebugInfo]):
+    if a is None and b is not None:
+        return b
+    if b is None and a is not None:
+        return a
+
+    if a.filename != b.filename:
+        # TODO: Support multiple files in debuginfo
+        return b
+
+    a_end_line = a.end_line if a.end_line >= 0 else a.start_line
+    b_end_line = b.end_line if b.end_line >= 0 else b.start_line
+    a_end_col = a.end_column if a.end_column >= 0 else a.start_column
+    b_end_col = b.end_column if b.end_column >= 0 else b.start_column
+
+    return dace.DebugInfo(
+        start_line=min(a.start_line, b.start_line),
+        start_column=min(a.start_column, b.start_column),
+        end_line=max(a_end_line, b_end_line),
+        end_column=max(a_end_col, b_end_col),
+        filename=a.filename,
+    )
diff --git a/dace/transformation/helpers.py b/dace/transformation/helpers.py
index b7bf49e62b..7824030e5c 100644
--- a/dace/transformation/helpers.py
+++ b/dace/transformation/helpers.py
@@ -688,6 +688,9 @@ def state_fission(subgraph: graph.SubgraphView, label: Optional[str] = None) ->
     for e in orig_edges:
         newstate.add_edge(new_nodes[e.src], e.src_conn, new_nodes[e.dst], e.dst_conn, e.data)
 
+    for bn in boundary_nodes:
+        bn._in_connectors.clear()
+
     return newstate
 
 
diff --git a/dace/transformation/interstate/loop_to_map.py b/dace/transformation/interstate/loop_to_map.py
index 39410f2547..58b9d51c59 100644
--- a/dace/transformation/interstate/loop_to_map.py
+++ b/dace/transformation/interstate/loop_to_map.py
@@ -450,7 +450,7 @@ def apply(self, _, sdfg: sd.SDFG):
                     increment_edge = sdfg.add_edge(new_body, e.dst, e.data)
 
 
-            elif 1 < self.expr_index <= 3:  # Rotated loop
+            elif 1 < self.expr_index <= 3 or 5 <= self.expr_index <= 7:  # Rotated loop
                 entrystate = self.entry_state
                 latch = self.loop_latch
 
@@ -668,7 +668,8 @@ def apply(self, _, sdfg: sd.SDFG):
             body.add_nedge(entry, exit, memlet.Memlet())
 
         # Get rid of the loop exit condition edge (it will be readded below)
-        sdfg.remove_edge(after_edge)
+        if self.expr_index not in (5, 6, 7):
+            sdfg.remove_edge(after_edge)
 
         # Remove the assignment on the edge to the guard
         for e in [init_edge, increment_edge]:
diff --git a/dace/transformation/interstate/multistate_inline.py b/dace/transformation/interstate/multistate_inline.py
index f637f479dc..84b8a82c75 100644
--- a/dace/transformation/interstate/multistate_inline.py
+++ b/dace/transformation/interstate/multistate_inline.py
@@ -149,6 +149,9 @@ def apply(self, outer_state: SDFGState, sdfg: SDFG):
         for loc, code in nsdfg.exit_code.items():
             sdfg.append_exit_code(code.code, loc)
 
+        # Callbacks and other types
+        sdfg._callback_mapping.update(nsdfg.callback_mapping)
+
         # Environments
         for nstate in nsdfg.nodes():
             for node in nstate.nodes():
diff --git a/dace/transformation/interstate/sdfg_nesting.py b/dace/transformation/interstate/sdfg_nesting.py
index 622dfe5595..7b64e49869 100644
--- a/dace/transformation/interstate/sdfg_nesting.py
+++ b/dace/transformation/interstate/sdfg_nesting.py
@@ -263,6 +263,9 @@ def apply(self, state: SDFGState, sdfg: SDFG):
         for loc, code in nsdfg.exit_code.items():
             sdfg.append_exit_code(code.code, loc)
 
+        # Callbacks and other types
+        sdfg._callback_mapping.update(nsdfg.callback_mapping)
+
         # Environments
         for node in nstate.nodes():
             if isinstance(node, nodes.CodeNode):
diff --git a/dace/transformation/interstate/state_fusion.py b/dace/transformation/interstate/state_fusion.py
index 3abbe085f5..dbdf7642bd 100644
--- a/dace/transformation/interstate/state_fusion.py
+++ b/dace/transformation/interstate/state_fusion.py
@@ -306,6 +306,15 @@ def can_be_applied(self, graph, expr_index, sdfg, permissive=False):
             resulting_ccs: List[CCDesc] = StateFusion.find_fused_components(first_cc_input, first_cc_output,
                                                                             second_cc_input, second_cc_output)
 
+            if len(resulting_ccs) > 1:
+                # Side-effect tasklets cannot be fused if could lead to data races
+                for node in first_state.nodes():
+                    if isinstance(node, nodes.CodeNode) and getattr(node, 'side_effects', False):
+                        return False
+                for node in second_state.nodes():
+                    if isinstance(node, nodes.CodeNode) and getattr(node, 'side_effects', False):
+                        return False
+
             # Check for data races
             for fused_cc in resulting_ccs:
                 # Write-Write hazard - data is output of both first and second
diff --git a/dace/transformation/passes/analysis/analysis.py b/dace/transformation/passes/analysis/analysis.py
index 095319f807..cc0d95c1d8 100644
--- a/dace/transformation/passes/analysis/analysis.py
+++ b/dace/transformation/passes/analysis/analysis.py
@@ -1,12 +1,14 @@
 # Copyright 2019-2024 ETH Zurich and the DaCe authors. All rights reserved.
 
-from collections import defaultdict
+from collections import defaultdict, deque
+from dataclasses import dataclass
 from dace.sdfg.state import ControlFlowBlock, ControlFlowRegion, LoopRegion
 from dace.transformation import pass_pipeline as ppl, transformation
 from dace import SDFG, SDFGState, properties, InterstateEdge, Memlet, data as dt, symbolic
 from dace.sdfg.graph import Edge
-from dace.sdfg import nodes as nd
+from dace.sdfg import nodes as nd, utils as sdutil
 from dace.sdfg.analysis import cfg
+from dace.sdfg.propagation import align_memlet
 from typing import Dict, Set, Tuple, Any, Optional, Union
 import networkx as nx
 from networkx.algorithms import shortest_paths as nxsp
@@ -632,6 +634,7 @@ def apply_pass(self, top_sdfg: SDFG, _) -> Dict[int, Dict[str, Set[Memlet]]]:
         return top_result
 
 
+@dataclass(unsafe_hash=True)
 @properties.make_properties
 @transformation.experimental_cfg_block_compatible
 class FindReferenceSources(ppl.Pass):
@@ -642,6 +645,9 @@ class FindReferenceSources(ppl.Pass):
 
     CATEGORY: str = 'Analysis'
 
+    trace_through_code = properties.Property(dtype=bool, default=False, desc='Trace inputs through tasklets.')
+    recursive = properties.Property(dtype=bool, default=False, desc='Add reference of reference dependencies.')
+
     def modifies(self) -> ppl.Modifies:
         return ppl.Modifies.Nothing
 
@@ -658,6 +664,7 @@ def apply_pass(self, top_sdfg: SDFG, _) -> Dict[int, Dict[str, Set[Union[Memlet,
             result: Dict[str, Set[Memlet]] = defaultdict(set)
             reference_descs = set(k for k, v in sdfg.arrays.items() if isinstance(v, dt.Reference))
             for state in sdfg.states():
+                code_sources: Dict[str, Set[nd.CodeNode]] = defaultdict(set)
                 for anode in state.data_nodes():
                     if anode.data not in reference_descs:
                         continue
@@ -668,9 +675,51 @@ def apply_pass(self, top_sdfg: SDFG, _) -> Dict[int, Dict[str, Set[Union[Memlet,
                         if isinstance(true_src, nd.CodeNode):
                             # Code  -> Reference
                             result[anode.data].add(true_src)
+                            code_sources[anode.data].add(true_src)
                         else:
                             # Array -> Reference
-                            result[anode.data].add(e.data)
+                            result[anode.data].add(align_memlet(state, e, dst=False))
+
+                            # If array is view, add view targets
+                            view_targets = sdutil.get_all_view_edges(state, true_src)
+                            for te in view_targets:
+                                result[anode.data].add(align_memlet(state, te, dst=False))
+
+                        if 'views' in anode.out_connectors:  # Reference and view
+                            out_edge, = state.out_edges_by_connector(anode, 'views')
+                            if isinstance(out_edge.dst, nd.AccessNode):
+                                view_targets = sdutil.get_all_view_nodes(state, out_edge.dst)
+                            for target in view_targets:
+                                if isinstance(true_src, nd.CodeNode):
+                                    # Code  -> Reference
+                                    result[target.data].add(true_src)
+                                    code_sources[target.data].add(true_src)
+                                else:
+                                    # Array -> Reference
+                                    result[target.data].add(align_memlet(state, e, dst=False))
+
+                # Trace back through code nodes
+                if self.trace_through_code:
+                    for name, codes in code_sources.items():
+                        sources = deque(codes)
+                        while sources:
+                            src = sources.pop()
+                            if isinstance(src, nd.CodeNode):
+                                for e in state.in_edges(src):
+                                    true_src = state.memlet_path(e)[0].src
+                                    if isinstance(true_src, nd.CodeNode):
+                                        # Keep traversing backwards
+                                        sources.append(true_src)
+                                    else:
+                                        result[name].add(e.data)
+
+            # Recursively add dependencies of reference dependencies
+            if self.recursive:
+                for k, v in result.items():
+                    for src in list(v):
+                        if not isinstance(v, nd.CodeNode) and src.data in result:
+                            v.update(result[src.data])
+
             top_result[sdfg.cfg_id] = result
         return top_result
 
diff --git a/dace/transformation/passes/pattern_matching.py b/dace/transformation/passes/pattern_matching.py
index a046a557ce..faa011f7d9 100644
--- a/dace/transformation/passes/pattern_matching.py
+++ b/dace/transformation/passes/pattern_matching.py
@@ -124,6 +124,7 @@ def apply_pass(self, sdfg: SDFG, pipeline_results: Dict[str, Any]) -> Dict[str,
 
             # Set previous pipeline results
             match._pipeline_results = pipeline_results
+            match.permissive = self.permissive
 
             result = match.apply(graph, tcfg.sdfg)
             applied_transformations[type(match).__name__].append(result)
@@ -177,6 +178,7 @@ def _apply_and_validate(self, match: xf.PatternTransformation, sdfg: SDFG, start
 
         # Set previous pipeline results
         match._pipeline_results = pipeline_results
+        match.permissive = self.permissive
 
         if self.validate_all:
             match_name = match.print_match(tcfg)
diff --git a/dace/transformation/passes/scalar_to_symbol.py b/dace/transformation/passes/scalar_to_symbol.py
index a0cb08ea0c..33712c8a1c 100644
--- a/dace/transformation/passes/scalar_to_symbol.py
+++ b/dace/transformation/passes/scalar_to_symbol.py
@@ -86,6 +86,8 @@ def find_promotable_scalars(sdfg: sd.SDFG, transients_only: bool = True, integer
 
     # General array checks
     for aname, desc in sdfg.arrays.items():
+        if isinstance(desc, (dt.View, dt.StructureView)):
+            continue
         if (transients_only and not desc.transient) or isinstance(desc, dt.Stream):
             continue
         if desc.total_size != 1:
@@ -185,6 +187,9 @@ def find_promotable_scalars(sdfg: sd.SDFG, transients_only: bool = True, integer
                 else:
                     # Check that tasklets have only one statement
                     cb: props.CodeBlock = edge.src.code
+                    if edge.src.has_side_effects(sdfg):
+                        candidates.remove(candidate)
+                        continue
                     if cb.language is dtypes.Language.Python:
                         if (len(cb.code) > 1 or not isinstance(cb.code[0], ast.Assign)):
                             candidates.remove(candidate)
@@ -314,22 +319,25 @@ def __init__(self, in_edges: Dict[str, mm.Memlet], out_edges: Dict[str, mm.Memle
         """
         self.in_edges = in_edges
         self.out_edges = out_edges
+        self.arrays = {k: sdfg.arrays[v.data] for k, v in in_edges.items() if k is not None}
+        self.arrays.update({k: sdfg.arrays[v.data] for k, v in out_edges.items() if k is not None})
         self.sdfg = sdfg
         self.defined = defined_syms
+        self.connector_names = set(in_edges.keys()) | set(out_edges.keys())
         self.in_mapping: Dict[str, Tuple[str, subsets.Range]] = {}
         self.out_mapping: Dict[str, Tuple[str, subsets.Range]] = {}
         self.do_not_remove: Set[str] = set()
-        self.latest: DefaultDict[str, int] = collections.defaultdict(int)
 
     def visit_Subscript(self, node: ast.Subscript) -> Any:
         # Convert subscript to symbol name
         node = self.generic_visit(node)
         node_name = astutils.rname(node)
         if node_name in self.in_edges:
-            self.latest[node_name] += 1
-            new_name = f'{node_name}_{self.latest[node_name]}'
+            new_name = dt.find_new_name(node_name, self.connector_names)
+            self.connector_names.add(new_name)
+
             orig_subset = self.in_edges[node_name].subset
-            subset = orig_subset.compose(subsets.Range(astutils.subscript_to_slice(node, self.sdfg.arrays)[1]))
+            subset = orig_subset.compose(subsets.Range(astutils.subscript_to_slice(node, self.arrays)[1]))
             # Check if range can be collapsed
             if _range_is_promotable(subset, self.defined):
                 self.in_mapping[new_name] = (node_name, subset)
@@ -337,10 +345,11 @@ def visit_Subscript(self, node: ast.Subscript) -> Any:
             else:
                 self.do_not_remove.add(node_name)
         elif node_name in self.out_edges:
-            self.latest[node_name] += 1
-            new_name = f'{node_name}_{self.latest[node_name]}'
+            new_name = dt.find_new_name(node_name, self.connector_names)
+            self.connector_names.add(new_name)
+
             orig_subset = self.out_edges[node_name].subset
-            subset = orig_subset.compose(subsets.Range(astutils.subscript_to_slice(node, self.sdfg.arrays)[1]))
+            subset = orig_subset.compose(subsets.Range(astutils.subscript_to_slice(node, self.arrays)[1]))
             # Check if range can be collapsed
             if _range_is_promotable(subset, self.defined):
                 self.out_mapping[new_name] = (node_name, subset)
@@ -649,6 +658,8 @@ def apply_pass(self, sdfg: SDFG, _: Dict[Any, Any]) -> Set[str]:
                 tasklet_inputs = [e.src for e in state.in_edges(input)]
                 # Step 2.1
                 new_state = xfh.state_fission(gr.SubgraphView(state, set([input, node] + tasklet_inputs)))
+                if state.edges_between(input, node):  # Edge still there after fission, remove manually
+                    state.remove_edge_and_connectors(state.edges_between(input, node)[0])
                 new_isedge: sd.InterstateEdge = new_state.parent_graph.out_edges(new_state)[0]
                 # Step 2.2
                 node: nodes.AccessNode = new_state.sink_nodes()[0]
diff --git a/tests/transformations/tasklet_fusion_test.py b/tests/transformations/tasklet_fusion_test.py
index c621ee38d4..7227056f4c 100644
--- a/tests/transformations/tasklet_fusion_test.py
+++ b/tests/transformations/tasklet_fusion_test.py
@@ -287,9 +287,37 @@ def sdfg_intermediate_transients(A: dace.float32[10], B: dace.float32[10]):
             applied = True
             break
 
-    assert applied
-    assert len([node for node in sdfg.start_state.data_nodes() if node.data == "tmp"]) == 1
-    assert "tmp" in sdfg.arrays
+    # tmp is used twice, so tasklet fusion should not apply
+    assert not applied
+
+
+def test_transient_in_different_state():
+
+    @dace.program
+    def sdfg_intermediate_transients(A: dace.float32[10], B: dace.float32[10]):
+        tmp = dace.define_local_scalar(dace.float32)
+
+        # Use tmp in different states to test removal of data
+        if B[0] < 0:
+            tmp = A[0] - 1
+            B[0] = tmp
+        else:
+            tmp = A[0] + 1
+            B[0] = tmp
+
+    sdfg = sdfg_intermediate_transients.to_sdfg(simplify=True)
+    assert len([node for state in sdfg.states() for node in state.data_nodes() if node.data == "tmp"]) == 2
+
+    xforms = Optimizer(sdfg=sdfg).get_pattern_matches(patterns=(TaskletFusion, ))
+    applied = False
+    for xform in xforms:
+        if xform.data.data == "tmp":
+            xform.apply(sdfg.start_state, sdfg)
+            applied = True
+            break
+
+    # tmp is used twice, so tasklet fusion should not apply
+    assert not applied
 
 
 if __name__ == '__main__':
@@ -304,3 +332,4 @@ def sdfg_intermediate_transients(A: dace.float32[10], B: dace.float32[10]):
     test_map_with_tasklets(language='CPP', with_data=True)
     test_none_connector()
     test_intermediate_transients()
+    test_transient_in_different_state()

From d7abf06ec0a72cd313086495bac619966a9535a6 Mon Sep 17 00:00:00 2001
From: Pratyai Mazumder <pratyai.mazumder@gmail.com>
Date: Tue, 5 Nov 2024 02:20:00 +0100
Subject: [PATCH 13/33] Rename FORTRAN frontend tests (#1729)

Example:
https://github.com/spcl/dace/actions/runs/11669534375/job/32491697698
runs only a small number of tests from `tests/fortran` (24 to be
precise, while after this change, it goes up to 75).
---
 tests/fortran/{intrinsic_all.py => intrinsic_all_test.py}         | 0
 tests/fortran/{intrinsic_any.py => intrinsic_any_test.py}         | 0
 tests/fortran/{intrinsic_count.py => intrinsic_count_test.py}     | 0
 tests/fortran/{intrinsic_merge.py => intrinsic_merge_test.py}     | 0
 .../{intrinsic_minmaxval.py => intrinsic_minmaxval_test.py}       | 0
 tests/fortran/{intrinsic_product.py => intrinsic_product_test.py} | 0
 tests/fortran/{intrinsic_sum.py => intrinsic_sum_test.py}         | 0
 tests/fortran/{offset_normalizer.py => offset_normalizer_test.py} | 0
 tests/fortran/{scope_arrays.py => scope_arrays_test.py}           | 0
 .../fortran/{sum_to_loop_offset.py => sum_to_loop_offset_test.py} | 0
 10 files changed, 0 insertions(+), 0 deletions(-)
 rename tests/fortran/{intrinsic_all.py => intrinsic_all_test.py} (100%)
 rename tests/fortran/{intrinsic_any.py => intrinsic_any_test.py} (100%)
 rename tests/fortran/{intrinsic_count.py => intrinsic_count_test.py} (100%)
 rename tests/fortran/{intrinsic_merge.py => intrinsic_merge_test.py} (100%)
 rename tests/fortran/{intrinsic_minmaxval.py => intrinsic_minmaxval_test.py} (100%)
 rename tests/fortran/{intrinsic_product.py => intrinsic_product_test.py} (100%)
 rename tests/fortran/{intrinsic_sum.py => intrinsic_sum_test.py} (100%)
 rename tests/fortran/{offset_normalizer.py => offset_normalizer_test.py} (100%)
 rename tests/fortran/{scope_arrays.py => scope_arrays_test.py} (100%)
 rename tests/fortran/{sum_to_loop_offset.py => sum_to_loop_offset_test.py} (100%)

diff --git a/tests/fortran/intrinsic_all.py b/tests/fortran/intrinsic_all_test.py
similarity index 100%
rename from tests/fortran/intrinsic_all.py
rename to tests/fortran/intrinsic_all_test.py
diff --git a/tests/fortran/intrinsic_any.py b/tests/fortran/intrinsic_any_test.py
similarity index 100%
rename from tests/fortran/intrinsic_any.py
rename to tests/fortran/intrinsic_any_test.py
diff --git a/tests/fortran/intrinsic_count.py b/tests/fortran/intrinsic_count_test.py
similarity index 100%
rename from tests/fortran/intrinsic_count.py
rename to tests/fortran/intrinsic_count_test.py
diff --git a/tests/fortran/intrinsic_merge.py b/tests/fortran/intrinsic_merge_test.py
similarity index 100%
rename from tests/fortran/intrinsic_merge.py
rename to tests/fortran/intrinsic_merge_test.py
diff --git a/tests/fortran/intrinsic_minmaxval.py b/tests/fortran/intrinsic_minmaxval_test.py
similarity index 100%
rename from tests/fortran/intrinsic_minmaxval.py
rename to tests/fortran/intrinsic_minmaxval_test.py
diff --git a/tests/fortran/intrinsic_product.py b/tests/fortran/intrinsic_product_test.py
similarity index 100%
rename from tests/fortran/intrinsic_product.py
rename to tests/fortran/intrinsic_product_test.py
diff --git a/tests/fortran/intrinsic_sum.py b/tests/fortran/intrinsic_sum_test.py
similarity index 100%
rename from tests/fortran/intrinsic_sum.py
rename to tests/fortran/intrinsic_sum_test.py
diff --git a/tests/fortran/offset_normalizer.py b/tests/fortran/offset_normalizer_test.py
similarity index 100%
rename from tests/fortran/offset_normalizer.py
rename to tests/fortran/offset_normalizer_test.py
diff --git a/tests/fortran/scope_arrays.py b/tests/fortran/scope_arrays_test.py
similarity index 100%
rename from tests/fortran/scope_arrays.py
rename to tests/fortran/scope_arrays_test.py
diff --git a/tests/fortran/sum_to_loop_offset.py b/tests/fortran/sum_to_loop_offset_test.py
similarity index 100%
rename from tests/fortran/sum_to_loop_offset.py
rename to tests/fortran/sum_to_loop_offset_test.py

From 15544216ed3b05444969f0ce0bdb31eb5d51afdc Mon Sep 17 00:00:00 2001
From: Yakup Koray Budanaz <budanaz.yakup@gmail.com>
Date: Tue, 5 Nov 2024 22:28:51 +0100
Subject: [PATCH 14/33] Add back clang-format support (#1732)

Add back clang-format.

I generated with a style file, without a style file, and without clang
format (uninstalled clang-format for this). SDFGs generate. I can add
tests.
---
 dace/codegen/compiler.py | 15 ++++++++++++++-
 dace/config_schema.yml   | 28 +++++++++++++++++++++-------
 2 files changed, 35 insertions(+), 8 deletions(-)

diff --git a/dace/codegen/compiler.py b/dace/codegen/compiler.py
index 236f832cac..927c59d19d 100644
--- a/dace/codegen/compiler.py
+++ b/dace/codegen/compiler.py
@@ -13,6 +13,7 @@
 import subprocess
 import re
 from typing import Any, Callable, Dict, List, Set, Tuple, TypeVar, Union
+import warnings
 
 import dace
 from dace.config import Config
@@ -57,6 +58,18 @@ def generate_program_folder(sdfg, code_objects: List[CodeObject], out_path: str,
         code_path = os.path.join(target_folder, basename)
         clean_code = code_object.clean_code
 
+        if Config.get_bool('compiler', 'format_code'):
+            config_file = Config.get('compiler', 'format_config_file')
+            if config_file is not None and config_file != "":
+                run_arg_list = ['clang-format', f"-style=file:{config_file}"]
+            else:
+                run_arg_list = ['clang-format']
+            result = subprocess.run(run_arg_list, input=clean_code, text=True, capture_output=True)
+            if result.returncode or result.stderr:
+                warnings.warn(f'clang-format failed to run: {result.stderr}')
+            else:
+                clean_code = result.stdout
+
         # Save the file only if it changed (keeps old timestamps and saves
         # build time)
         if not identical_file_exists(code_path, clean_code):
@@ -260,7 +273,7 @@ def get_environment_flags(environments) -> Tuple[List[str], Set[str]]:
     """
     Returns the CMake environment and linkage flags associated with the
     given input environments/libraries.
-    
+
     :param environments: A list of ``@dace.library.environment``-decorated
                          classes.
     :return: A 2-tuple of (environment CMake flags, linkage CMake flags)
diff --git a/dace/config_schema.yml b/dace/config_schema.yml
index 7afb06a50a..b5a7914018 100644
--- a/dace/config_schema.yml
+++ b/dace/config_schema.yml
@@ -173,6 +173,20 @@ required:
                     The typename of this struct is derived by appending this value to the SDFG's name.
                     Note that the suffix may only contains letters, digits and underscores.
 
+            format_code:
+                type: bool
+                default: false
+                title: Format code with `clang-format`
+                description: >
+                    Formats the generated code with `clang-format` before saving the files.
+
+            format_config_file:
+                type: str
+                default: ""
+                title: Path the clang-format file
+                description: >
+                    Clang-format file to be used by clang-format, only used if format_code is true
+
             default_data_types:
                 type : str
                 default: Python
@@ -474,7 +488,7 @@ required:
                         title: Detect parts of an SDFG that can run in parallel
                         description: >
                             If set to false, DaCe will place each weakly connected
-                            component found in an SDFG state in a different Kernel/Processing Element. 
+                            component found in an SDFG state in a different Kernel/Processing Element.
                             If true, a heuristic will further inspect each independent component
                             for other parallelism opportunities (e.g., branches of the SDFG
                             that can be executed in parallel), creating the corresponding kernels.
@@ -800,7 +814,7 @@ required:
                 default: false
                 title: Check arguments on SDFG call
                 description: >
-                    Perform an early type check on arguments passed to an SDFG when called directly (from 
+                    Perform an early type check on arguments passed to an SDFG when called directly (from
                     ``SDFG.__call__``). Another type check is performed when calling compiled SDFGs.
 
             avoid_wcr:
@@ -835,18 +849,18 @@ required:
         title: Compiled cache entry naming policy
         description: >
             Determine the name of the generated ``.dacecache`` folder:
-            
-            
+
+
             * ``name`` uses the name of the SDFG directly, causing it to be
             overridden by other programs using the same SDFG name.
-            
+
             * ``hash`` uses a mangled name based on the hash of the SDFG, such that
             any change to the SDFG will generate a different cache folder.
-            
+
             * ``unique`` uses a name based on the currently running Python process
             at code generation time, such that no caching or clashes can happen
             between different processes or subsequent invocations of Python.
-            
+
             * ``single`` uses a single cache folder for all SDFGs, saving space and
             potentially build time, but disallows executing SDFGs in parallel
             and caching of more than one simultaneous SDFG.

From 163366d7a1295e6f2da70357428bf301b138e1cf Mon Sep 17 00:00:00 2001
From: Philipp Schaad <schaad.phil@gmail.com>
Date: Wed, 6 Nov 2024 09:07:04 +0100
Subject: [PATCH 15/33] Fix problem with struct reads on interstate edges
 (#1512)

Co-authored-by: Alexandros Nikolaos Ziogas <alexandros.ziogas@inf.ethz.ch>
Co-authored-by: Tal Ben-Nun <tbennun@users.noreply.github.com>
Co-authored-by: alexnick83 <31545860+alexnick83@users.noreply.github.com>
---
 dace/codegen/targets/cpp.py               | 10 ++++
 dace/codegen/targets/cpu.py               |  8 ++-
 dace/data.py                              |  9 +++-
 dace/transformation/auto/auto_optimize.py |  4 ++
 tests/sdfg/data/structure_test.py         | 62 +++++++++++++++++++++++
 5 files changed, 90 insertions(+), 3 deletions(-)

diff --git a/dace/codegen/targets/cpp.py b/dace/codegen/targets/cpp.py
index c34c829c31..86942874d1 100644
--- a/dace/codegen/targets/cpp.py
+++ b/dace/codegen/targets/cpp.py
@@ -1036,6 +1036,16 @@ def _Name(self, t: ast.Name):
         # Replace values with their code-generated names (for example, persistent arrays)
         desc = self.sdfg.arrays[t.id]
         self.write(ptr(t.id, desc, self.sdfg, self.codegen))
+    
+    def _Attribute(self, t: ast.Attribute):
+        from dace.frontend.python.astutils import rname
+        name = rname(t)
+        if name not in self.sdfg.arrays:
+            return super()._Attribute(t)
+
+        # Replace values with their code-generated names (for example, persistent arrays)
+        desc = self.sdfg.arrays[name]
+        self.write(ptr(name, desc, self.sdfg, self.codegen))
 
     def _Subscript(self, t: ast.Subscript):
         from dace.frontend.python.astutils import subscript_to_slice
diff --git a/dace/codegen/targets/cpu.py b/dace/codegen/targets/cpu.py
index 51daaa432b..160855458d 100644
--- a/dace/codegen/targets/cpu.py
+++ b/dace/codegen/targets/cpu.py
@@ -406,8 +406,12 @@ def allocate_array(self, sdfg: SDFG, cfg: ControlFlowRegion, dfg: StateSubgraphV
                         ctypedef = dtypes.pointer(v.dtype).ctype if isinstance(v, data.Array) else v.dtype.ctype
                         defined_type = DefinedType.Scalar if isinstance(v, data.Scalar) else DefinedType.Pointer
                         self._dispatcher.declared_arrays.add(f"{name}->{k}", defined_type, ctypedef)
-                        self.allocate_array(sdfg, cfg, dfg, state_id, nodes.AccessNode(f"{name}.{k}"), v,
-                                            function_stream, declaration_stream, allocation_stream)
+                        if isinstance(v, data.Scalar):
+                            # NOTE: Scalar members are already defined in the struct definition.
+                            self._dispatcher.defined_vars.add(f"{name}->{k}", defined_type, ctypedef)
+                        else:
+                            self.allocate_array(sdfg, cfg, dfg, state_id, nodes.AccessNode(f"{name}.{k}"), v,
+                                                function_stream, declaration_stream, allocation_stream)
             return
         if isinstance(nodedesc, data.View):
             return self.allocate_view(sdfg, cfg, dfg, state_id, node, function_stream, declaration_stream,
diff --git a/dace/data.py b/dace/data.py
index a07fe42083..9749411fe6 100644
--- a/dace/data.py
+++ b/dace/data.py
@@ -167,9 +167,16 @@ class Data:
         Examples: Arrays, Streams, custom arrays (e.g., sparse matrices).
     """
 
+    def _transient_setter(self, value):
+        self._transient = value
+        if isinstance(self, Structure):
+            for _, v in self.members.items():
+                if isinstance(v, Data):
+                    v.transient = value
+
     dtype = TypeClassProperty(default=dtypes.int32, choices=dtypes.Typeclasses)
     shape = ShapeProperty(default=[])
-    transient = Property(dtype=bool, default=False)
+    transient = Property(dtype=bool, default=False, setter=_transient_setter)
     storage = EnumProperty(dtype=dtypes.StorageType, desc="Storage location", default=dtypes.StorageType.Default)
     lifetime = EnumProperty(dtype=dtypes.AllocationLifetime,
                             desc='Data allocation span',
diff --git a/dace/transformation/auto/auto_optimize.py b/dace/transformation/auto/auto_optimize.py
index 7bced3bec9..0a1371ae68 100644
--- a/dace/transformation/auto/auto_optimize.py
+++ b/dace/transformation/auto/auto_optimize.py
@@ -474,6 +474,10 @@ def make_transients_persistent(sdfg: SDFG,
                     not_persistent.add(dnode.data)
                     continue
                 desc = dnode.desc(nsdfg)
+                # Only convert what is not a member of a non-persistent struct.
+                if (dnode.root_data != dnode.data and
+                    nsdfg.arrays[dnode.root_data].lifetime != dtypes.AllocationLifetime.Persistent):
+                    continue
                 # Only convert arrays and scalars that are not registers
                 if not desc.transient or type(desc) not in {dt.Array, dt.Scalar}:
                     not_persistent.add(dnode.data)
diff --git a/tests/sdfg/data/structure_test.py b/tests/sdfg/data/structure_test.py
index 55e3a936a7..f2ab0e51a2 100644
--- a/tests/sdfg/data/structure_test.py
+++ b/tests/sdfg/data/structure_test.py
@@ -543,6 +543,67 @@ def test_direct_read_nested_structure():
     assert np.allclose(B, ref)
 
 
+def test_read_struct_member_interstate_edge():
+    sdfg = dace.SDFG('test_read_struct_member_interstate_edge')
+
+    struct_data = dace.data.Structure({
+        'start': dace.data.Scalar(dace.int32),
+        'stop': dace.data.Scalar(dace.int32),
+    }, 't_indices')
+    struct_data.transient = True
+    sdfg.add_datadesc('indices', struct_data)
+    sdfg.add_array('A', [20], dace.int32, transient=False)
+    _, desc_start_in = sdfg.add_scalar('start_in', dace.int32, transient=False)
+    _, desc_stop_in = sdfg.add_scalar('stop_in', dace.int32, transient=False)
+    _, v_start = sdfg.add_view('v_start', [1], dace.int32)
+    _, v_stop = sdfg.add_view('v_stop', [1], dace.int32)
+
+    init = sdfg.add_state('init', is_start_block=True)
+    init2 = sdfg.add_state('init', is_start_block=True)
+    guard = sdfg.add_state('guard')
+    body = sdfg.add_state('guard')
+    tail = sdfg.add_state('guard')
+    sdfg.add_edge(init, init2, dace.InterstateEdge())
+    sdfg.add_edge(init2, guard, dace.InterstateEdge(assignments={'i': 'indices.start'}))
+    sdfg.add_edge(guard, body, dace.InterstateEdge(condition='i <= indices.stop'))
+    sdfg.add_edge(body, guard, dace.InterstateEdge(assignments={'i': '(i + 1)'}))
+    sdfg.add_edge(guard, tail, dace.InterstateEdge(condition='not (i <= indices.stop)'))
+
+    in_start_access = init.add_access('start_in')
+    t1 = init.add_tasklet('t1', {'i1'}, {'o1'}, 'o1 = i1')
+    start_access = init.add_access('v_start')
+    ind_access1 = init.add_access('indices')
+    init.add_edge(in_start_access, None, t1, 'i1', dace.Memlet.from_array('start_in', desc_start_in))
+    init.add_edge(t1, 'o1', start_access, None, dace.Memlet.from_array('v_start', v_start))
+    init.add_edge(start_access, 'views', ind_access1, None,
+                  dace.Memlet.from_array('indices.start', struct_data.members['start']))
+
+    in_stop_access = init2.add_access('stop_in')
+    t2 = init2.add_tasklet('t2', {'i1'}, {'o1'}, 'o1 = i1')
+    stop_access = init2.add_access('v_stop')
+    ind_access2 = init2.add_access('indices')
+    init2.add_edge(in_stop_access, None, t2, 'i1', dace.Memlet.from_array('stop_in', desc_stop_in))
+    init2.add_edge(t2, 'o1', stop_access, None, dace.Memlet.from_array('v_stop', v_stop))
+    init2.add_edge(stop_access, 'views', ind_access2, None,
+                   dace.Memlet.from_array('indices.stop', struct_data.members['stop']))
+
+    t3 = body.add_tasklet('t3', {}, {'o1'}, 'o1 = i')
+    a_access = body.add_access('A')
+    body.add_edge(t3, 'o1', a_access, None, dace.Memlet('A[i]'))
+
+    sdfg.validate()
+
+    arr = np.zeros((20,), dtype=np.int32)
+    arr_validate = np.zeros((20,), dtype=np.int32)
+    for i in range(11):
+        arr_validate[i] = i
+
+    c_sdfg = sdfg.compile()
+    c_sdfg(A=arr, start_in=0, stop_in=10)
+
+    assert np.allclose(arr, arr_validate)
+
+
 if __name__ == "__main__":
     test_read_structure()
     test_write_structure()
@@ -552,3 +613,4 @@ def test_direct_read_nested_structure():
     test_direct_read_structure()
     test_direct_read_nested_structure()
     test_direct_read_structure_loops()
+    test_read_struct_member_interstate_edge()

From 7c70423507dc37e877076d39d4fd80f16e312006 Mon Sep 17 00:00:00 2001
From: Roman Cattaneo <romanc@users.noreply.github.com>
Date: Wed, 6 Nov 2024 09:46:38 +0100
Subject: [PATCH 16/33] Quality of live: Improved error messages (#1731)

Small quality of live PR that improves two error messages. Especially if
the state was called `state` (as per default), it was hard to parse at
first sight


![image](https://github.com/user-attachments/assets/500cf100-57b8-4140-b4f7-d6cb0091829b)


For some reason, `yapf` was also changing the formatting of other code
parts. I thus made two commits

1. Format the two files that I was about to edit.
2. Improve the error messages in the freshly formatted files.

This allows to separate real changes from purely stylistic ones.

Would it be an idea to enforce linting with a GitHub Actions workflow?
I'm happy to write an issue about this (and contribute early next year).

---------

Co-authored-by: Roman Cattaneo <>
---
 dace/codegen/targets/cpp.py | 20 +++++++--------
 dace/sdfg/validation.py     | 49 +++++++++++++++++++------------------
 2 files changed, 35 insertions(+), 34 deletions(-)

diff --git a/dace/codegen/targets/cpp.py b/dace/codegen/targets/cpp.py
index 86942874d1..ed52bd093a 100644
--- a/dace/codegen/targets/cpp.py
+++ b/dace/codegen/targets/cpp.py
@@ -983,9 +983,10 @@ def unparse_tasklet(sdfg, cfg, state_id, dfg, node, function_stream, callsite_st
     # To prevent variables-redefinition, build dictionary with all the previously defined symbols
     defined_symbols = state_dfg.symbols_defined_at(node)
 
-    defined_symbols.update(
-        {k: v.dtype if hasattr(v, 'dtype') else dtypes.typeclass(type(v))
-         for k, v in sdfg.constants.items()})
+    defined_symbols.update({
+        k: v.dtype if hasattr(v, 'dtype') else dtypes.typeclass(type(v))
+        for k, v in sdfg.constants.items()
+    })
 
     for connector, (memlet, _, _, conntype) in memlets.items():
         if connector is not None:
@@ -1152,7 +1153,7 @@ def _subscript_expr(self, slicenode: ast.AST, target: str) -> symbolic.SymbolicT
             return sum(symbolic.pystr_to_symbolic(unparse(elt)) * s for elt, s in zip(elts, strides))
 
         if len(strides) != 1:
-            raise SyntaxError('Missing dimensions in expression (expected %d, got one)' % len(strides))
+            raise SyntaxError('Missing dimensions in expression (expected one, got %d)' % len(strides))
 
         try:
             return symbolic.pystr_to_symbolic(unparse(visited_slice)) * strides[0]
@@ -1289,8 +1290,7 @@ def visit_Name(self, node: ast.Name):
             if memlet.data in self.sdfg.arrays and self.sdfg.arrays[memlet.data].dtype == dtype:
                 return self.generic_visit(node)
             return ast.parse(f"{name}[0]").body[0].value
-        elif (self.allow_casts and (defined_type in (DefinedType.Stream, DefinedType.StreamArray))
-              and memlet.dynamic):
+        elif (self.allow_casts and (defined_type in (DefinedType.Stream, DefinedType.StreamArray)) and memlet.dynamic):
             return ast.parse(f"{name}.pop()").body[0].value
         else:
             return self.generic_visit(node)
@@ -1324,8 +1324,8 @@ def visit_BinOp(self, node: ast.BinOp):
                 evaluated_constant = symbolic.evaluate(unparsed, self.constants)
                 evaluated = symbolic.symstr(evaluated_constant, cpp_mode=True)
                 value = ast.parse(evaluated).body[0].value
-                if isinstance(evaluated_node, numbers.Number) and evaluated_node != (
-                        value.value if sys.version_info >= (3, 8) else value.n):
+                if isinstance(evaluated_node, numbers.Number) and evaluated_node != (value.value if sys.version_info
+                                                                                     >= (3, 8) else value.n):
                     raise TypeError
                 node.right = ast.parse(evaluated).body[0].value
             except (TypeError, AttributeError, NameError, KeyError, ValueError, SyntaxError):
@@ -1378,8 +1378,8 @@ def visit_Call(self, node):
 
 
 # TODO: This should be in the CUDA code generator. Add appropriate conditions to node dispatch predicate
-def presynchronize_streams(sdfg: SDFG, cfg: ControlFlowRegion, dfg: StateSubgraphView, state_id: int,
-                           node: nodes.Node, callsite_stream: CodeIOStream):
+def presynchronize_streams(sdfg: SDFG, cfg: ControlFlowRegion, dfg: StateSubgraphView, state_id: int, node: nodes.Node,
+                           callsite_stream: CodeIOStream):
     state_dfg: SDFGState = cfg.nodes()[state_id]
     if hasattr(node, "_cuda_stream") or is_devicelevel_gpu(sdfg, state_dfg, node):
         return
diff --git a/dace/sdfg/validation.py b/dace/sdfg/validation.py
index 0b1d946798..1f5c263206 100644
--- a/dace/sdfg/validation.py
+++ b/dace/sdfg/validation.py
@@ -119,9 +119,10 @@ def validate_control_flow_region(sdfg: 'SDFG',
             also_assigned = (syms & edge.data.assignments.keys()) - {aname}
             if also_assigned:
                 eid = region.edge_id(edge)
-                raise InvalidSDFGInterstateEdgeError(f'Race condition: inter-state assignment {aname} = {aval} uses '
-                                                     f'variables {also_assigned}, which are also modified in the same '
-                                                     'edge.', sdfg, eid)
+                raise InvalidSDFGInterstateEdgeError(
+                    f'Race condition: inter-state assignment {aname} = {aval} uses '
+                    f'variables {also_assigned}, which are also modified in the same '
+                    'edge.', sdfg, eid)
 
         # Add edge symbols into defined symbols
         symbols.update(issyms)
@@ -228,9 +229,7 @@ def validate_sdfg(sdfg: 'dace.sdfg.SDFG', references: Set[int] = None, **context
 
         # Check the names of data descriptors and co.
         seen_names: Set[str] = set()
-        for obj_names in [
-                sdfg.arrays.keys(), sdfg.symbols.keys(), sdfg._rdistrarrays.keys(), sdfg._subarrays.keys()
-        ]:
+        for obj_names in [sdfg.arrays.keys(), sdfg.symbols.keys(), sdfg._rdistrarrays.keys(), sdfg._subarrays.keys()]:
             if not seen_names.isdisjoint(obj_names):
                 raise InvalidSDFGError(
                     f'Found duplicated names: "{seen_names.intersection(obj_names)}". Please ensure '
@@ -242,15 +241,13 @@ def validate_sdfg(sdfg: 'dace.sdfg.SDFG', references: Set[int] = None, **context
             if const_name in sdfg.arrays:
                 if const_type != sdfg.arrays[const_name].dtype:
                     # This should actually be an error, but there is a lots of code that depends on it.
-                    warnings.warn(
-                        f'Mismatch between constant and data descriptor of "{const_name}", '
-                        f'expected to find "{const_type}" but found "{sdfg.arrays[const_name]}".')
+                    warnings.warn(f'Mismatch between constant and data descriptor of "{const_name}", '
+                                  f'expected to find "{const_type}" but found "{sdfg.arrays[const_name]}".')
             elif const_name in sdfg.symbols:
                 if const_type != sdfg.symbols[const_name]:
                     # This should actually be an error, but there is a lots of code that depends on it.
-                    warnings.warn(
-                        f'Mismatch between constant and symobl type of "{const_name}", '
-                        f'expected to find "{const_type}" but found "{sdfg.symbols[const_name]}".')
+                    warnings.warn(f'Mismatch between constant and symobl type of "{const_name}", '
+                                  f'expected to find "{const_type}" but found "{sdfg.symbols[const_name]}".')
             else:
                 warnings.warn(f'Found constant "{const_name}" that does not refer to an array or a symbol.')
 
@@ -388,8 +385,7 @@ def validate_state(state: 'dace.sdfg.SDFGState',
     from dace.sdfg import SDFG
     from dace.sdfg import nodes as nd
     from dace.sdfg import utils as sdutil
-    from dace.sdfg.scope import (is_devicelevel_fpga, is_devicelevel_gpu,
-                                 scope_contains_scope)
+    from dace.sdfg.scope import (is_devicelevel_fpga, is_devicelevel_gpu, scope_contains_scope)
 
     sdfg = sdfg or state.parent
     state_id = state_id if state_id is not None else state.parent_graph.node_id(state)
@@ -520,7 +516,7 @@ def validate_state(state: 'dace.sdfg.SDFGState',
                       # Streams do not need to be initialized
                       and not isinstance(arr, dt.Stream)):
                     if node.setzero == False:
-                        warnings.warn('WARNING: Use of uninitialized transient "%s" in state %s' %
+                        warnings.warn('WARNING: Use of uninitialized transient "%s" in state "%s"' %
                                       (node.data, state.label))
 
                 # Register initialized transients
@@ -854,19 +850,24 @@ def validate_state(state: 'dace.sdfg.SDFGState',
         read_accesses = defaultdict(list)
         for node in state.data_nodes():
             node_labels.append(node.label)
-            write_accesses[node.label].extend(
-                [{'subset': e.data.dst_subset, 'node': node, 'wcr': e.data.wcr} for e in state.in_edges(node)])
-            read_accesses[node.label].extend(
-                [{'subset': e.data.src_subset, 'node': node} for e in state.out_edges(node)])
+            write_accesses[node.label].extend([{
+                'subset': e.data.dst_subset,
+                'node': node,
+                'wcr': e.data.wcr
+            } for e in state.in_edges(node)])
+            read_accesses[node.label].extend([{
+                'subset': e.data.src_subset,
+                'node': node
+            } for e in state.out_edges(node)])
 
         for node_label in node_labels:
             writes = write_accesses[node_label]
             reads = read_accesses[node_label]
             # Check write-write data races.
             for i in range(len(writes)):
-                for j in range(i+1, len(writes)):
-                    same_or_unreachable_nodes = (writes[i]['node'] == writes[j]['node'] or
-                                                 not nx.has_path(state.nx, writes[i]['node'], writes[j]['node']))
+                for j in range(i + 1, len(writes)):
+                    same_or_unreachable_nodes = (writes[i]['node'] == writes[j]['node']
+                                                 or not nx.has_path(state.nx, writes[i]['node'], writes[j]['node']))
                     no_wcr = writes[i]['wcr'] is None and writes[j]['wcr'] is None
                     if same_or_unreachable_nodes and no_wcr:
                         subsets_intersect = subsets.intersects(writes[i]['subset'], writes[j]['subset'])
@@ -875,8 +876,8 @@ def validate_state(state: 'dace.sdfg.SDFGState',
             # Check read-write data races.
             for write in writes:
                 for read in reads:
-                    if (not nx.has_path(state.nx, read['node'], write['node']) and
-                        subsets.intersects(write['subset'], read['subset'])):
+                    if (not nx.has_path(state.nx, read['node'], write['node'])
+                            and subsets.intersects(write['subset'], read['subset'])):
                         warnings.warn(f'Memlet range overlap while writing to "{node}" in state "{state.label}"')
 
     ########################################

From 72ee7328c71b3012f35820986988b83b467098e2 Mon Sep 17 00:00:00 2001
From: Pratyai Mazumder <pratyai.mazumder@gmail.com>
Date: Wed, 6 Nov 2024 10:58:19 +0100
Subject: [PATCH 17/33] Cherry-picked a handful of intrinsic related commits
 out of `multi_sdfg` branch. (#1728)

These commits:
1. are chronologically early
2. fairly independent and touch a small number of files
3. thematically fit together.

This is a follow-up on the discussion about incrementally moving the
stable features from `multi_sdfg` branch into `main`. All of the commits
are cherry-picked to preserve the history and to have easy
fast-forwarding of the `multi_sdfg` branch.

Some commits had to be slightly modified to resolve the merge conflicts
during cherry-picking, but otherwise they are left as-is.

---------

Co-authored-by: Marcin Copik <mcopik@gmail.com>
---
 dace/frontend/fortran/ast_transforms.py |  27 +-
 dace/frontend/fortran/fortran_parser.py |  12 +-
 dace/frontend/fortran/intrinsics.py     | 529 ++++++++++++---
 dace/runtime/include/dace/math.h        |  39 ++
 tests/fortran/call_extract_test.py      |  39 ++
 tests/fortran/intrinsic_basic_test.py   |  98 +++
 tests/fortran/intrinsic_math_test.py    | 845 ++++++++++++++++++++++++
 7 files changed, 1475 insertions(+), 114 deletions(-)
 create mode 100644 tests/fortran/call_extract_test.py
 create mode 100644 tests/fortran/intrinsic_basic_test.py
 create mode 100644 tests/fortran/intrinsic_math_test.py

diff --git a/dace/frontend/fortran/ast_transforms.py b/dace/frontend/fortran/ast_transforms.py
index 0c96560fba..57508d6d90 100644
--- a/dace/frontend/fortran/ast_transforms.py
+++ b/dace/frontend/fortran/ast_transforms.py
@@ -184,7 +184,7 @@ def __init__(self, funcs=None):
 
         from dace.frontend.fortran.intrinsics import FortranIntrinsics
         self.excepted_funcs = [
-            "malloc", "exp", "pow", "sqrt", "cbrt", "max", "abs", "min", "__dace_sign", "tanh",
+            "malloc", "pow", "cbrt", "__dace_sign", "tanh", "atan2",
             "__dace_epsilon", *FortranIntrinsics.function_names()
         ]
 
@@ -220,7 +220,7 @@ def visit_Call_Expr_Node(self, node: ast_internal_classes.Call_Expr_Node):
 
         from dace.frontend.fortran.intrinsics import FortranIntrinsics
         if not stop and node.name.name not in [
-                "malloc", "exp", "pow", "sqrt", "cbrt", "max", "min", "abs", "tanh", "__dace_epsilon", *FortranIntrinsics.call_extraction_exemptions()
+                "malloc", "pow", "cbrt", "__dace_epsilon", *FortranIntrinsics.call_extraction_exemptions()
         ]:
             self.nodes.append(node)
         return self.generic_visit(node)
@@ -241,7 +241,7 @@ def __init__(self, count=0):
     def visit_Call_Expr_Node(self, node: ast_internal_classes.Call_Expr_Node):
 
         from dace.frontend.fortran.intrinsics import FortranIntrinsics
-        if node.name.name in ["malloc", "exp", "pow", "sqrt", "cbrt", "max", "min", "abs", "tanh", "__dace_epsilon", *FortranIntrinsics.call_extraction_exemptions()]:
+        if node.name.name in ["malloc", "pow", "cbrt",  "__dace_epsilon", *FortranIntrinsics.call_extraction_exemptions()]:
             return self.generic_visit(node)
         if hasattr(node, "subroutine"):
             if node.subroutine is True:
@@ -251,6 +251,11 @@ def visit_Call_Expr_Node(self, node: ast_internal_classes.Call_Expr_Node):
         else:
             self.count = self.count + 1
         tmp = self.count
+
+        for i, arg in enumerate(node.args):
+            # Ensure we allow to extract function calls from arguments
+            node.args[i] = self.visit(arg)
+
         return ast_internal_classes.Name_Node(name="tmp_call_" + str(tmp - 1))
 
     def visit_Execution_Part_Node(self, node: ast_internal_classes.Execution_Part_Node):
@@ -263,9 +268,13 @@ def visit_Execution_Part_Node(self, node: ast_internal_classes.Execution_Part_No
             for i in res:
                 if i == child:
                     res.pop(res.index(i))
-            temp = self.count
             if res is not None:
-                for i in range(0, len(res)):
+                # Variables are counted from 0...end, starting from main node, to all calls nested
+                # in main node arguments.
+                # However, we need to define nested ones first.
+                # We go in reverse order, counting from end-1 to 0.
+                temp = self.count + len(res) - 1
+                for i in reversed(range(0, len(res))):
 
                     newbody.append(
                         ast_internal_classes.Decl_Stmt_Node(vardecl=[
@@ -282,7 +291,7 @@ def visit_Execution_Part_Node(self, node: ast_internal_classes.Execution_Part_No
                                                                                             type=res[i].type),
                                                         rval=res[i],
                                                         line_number=child.line_number))
-                    temp = temp + 1
+                    temp = temp - 1
             if isinstance(child, ast_internal_classes.Call_Expr_Node):
                 new_args = []
                 if hasattr(child, "args"):
@@ -368,7 +377,8 @@ def __init__(self):
         self.nodes: List[ast_internal_classes.Array_Subscript_Node] = []
 
     def visit_Call_Expr_Node(self, node: ast_internal_classes.Call_Expr_Node):
-        if node.name.name in ["sqrt", "exp", "pow", "max", "min", "abs", "tanh"]:
+        from dace.frontend.fortran.intrinsics import FortranIntrinsics
+        if node.name.name in ["pow", "atan2", "tanh", *FortranIntrinsics.retained_function_names()]:
             return self.generic_visit(node)
         else:
             return
@@ -401,7 +411,8 @@ def __init__(self, ast: ast_internal_classes.FNode, normalize_offsets: bool = Fa
             self.scope_vars.visit(ast)
 
     def visit_Call_Expr_Node(self, node: ast_internal_classes.Call_Expr_Node):
-        if node.name.name in ["sqrt", "exp", "pow", "max", "min", "abs", "tanh"]:
+        from dace.frontend.fortran.intrinsics import FortranIntrinsics
+        if node.name.name in ["pow", "atan2", "tanh", *FortranIntrinsics.retained_function_names()]:
             return self.generic_visit(node)
         else:
             return node
diff --git a/dace/frontend/fortran/fortran_parser.py b/dace/frontend/fortran/fortran_parser.py
index 52344c141f..1cdecc99a8 100644
--- a/dace/frontend/fortran/fortran_parser.py
+++ b/dace/frontend/fortran/fortran_parser.py
@@ -818,7 +818,8 @@ def binop2sdfg(self, node: ast_internal_classes.BinOp_Node, sdfg: SDFG, cfg: Con
         calls.visit(node)
         if len(calls.nodes) == 1:
             augmented_call = calls.nodes[0]
-            if augmented_call.name.name not in ["sqrt", "exp", "pow", "max", "min", "abs", "tanh", "__dace_epsilon"]:
+            from dace.frontend.fortran.intrinsics import FortranIntrinsics
+            if augmented_call.name.name not in ["pow", "atan2", "tanh", "__dace_epsilon", *FortranIntrinsics.retained_function_names()]:
                 augmented_call.args.append(node.lval)
                 augmented_call.hasret = True
                 self.call2sdfg(augmented_call, sdfg, cfg)
@@ -1090,7 +1091,8 @@ def create_ast_from_string(
         program = ast_transforms.ArrayToLoop(program).visit(program)
 
         for transformation in own_ast.fortran_intrinsics().transformations():
-            program = transformation(program).visit(program)
+            transformation.initialize(program)
+            program = transformation.visit(program)
 
         program = ast_transforms.ForDeclarer().visit(program)
         program = ast_transforms.IndexExtractor(program, normalize_offsets).visit(program)
@@ -1126,7 +1128,8 @@ def create_sdfg_from_string(
     program = ast_transforms.ArrayToLoop(program).visit(program)
 
     for transformation in own_ast.fortran_intrinsics().transformations():
-        program = transformation(program).visit(program)
+        transformation.initialize(program)
+        program = transformation.visit(program)
 
     program = ast_transforms.ForDeclarer().visit(program)
     program = ast_transforms.IndexExtractor(program, normalize_offsets).visit(program)
@@ -1172,7 +1175,8 @@ def create_sdfg_from_fortran_file(source_string: str, use_experimental_cfg_block
     program = ast_transforms.ArrayToLoop(program).visit(program)
 
     for transformation in own_ast.fortran_intrinsics():
-        program = transformation(program).visit(program)
+        transformation.initialize(program)
+        program = transformation.visit(program)
 
     program = ast_transforms.ForDeclarer().visit(program)
     program = ast_transforms.IndexExtractor(program).visit(program)
diff --git a/dace/frontend/fortran/intrinsics.py b/dace/frontend/fortran/intrinsics.py
index c2e5afe79b..af44a8dfb5 100644
--- a/dace/frontend/fortran/intrinsics.py
+++ b/dace/frontend/fortran/intrinsics.py
@@ -2,6 +2,7 @@
 from abc import abstractmethod
 import copy
 import math
+from collections import namedtuple
 from typing import Any, List, Optional, Set, Tuple, Type
 
 from dace.frontend.fortran import ast_internal_classes
@@ -26,34 +27,175 @@ def replace(func_name: ast_internal_classes.Name_Node, args: ast_internal_classe
     def has_transformation() -> bool:
         return False
 
-class SelectedKind(IntrinsicTransformation):
+class IntrinsicNodeTransformer(NodeTransformer):
+
+    def initialize(self, ast):
+        # We need to rerun the assignment because transformations could have created
+        # new AST nodes
+        ParentScopeAssigner().visit(ast)
+        self.scope_vars = ScopeVarsDeclarations()
+        self.scope_vars.visit(ast)
+
+    @staticmethod
+    @abstractmethod
+    def func_name(self) -> str:
+        pass
+
+class DirectReplacement(IntrinsicTransformation):
+
+    Replacement = namedtuple("Replacement", "function")
+    Transformation = namedtuple("Transformation", "function")
+
+    class ASTTransformation(IntrinsicNodeTransformer):
+
+        def visit_BinOp_Node(self, binop_node: ast_internal_classes.BinOp_Node):
+
+            if not isinstance(binop_node.rval, ast_internal_classes.Call_Expr_Node):
+                return binop_node
+
+            node = binop_node.rval
+
+            name = node.name.name.split('__dace_')
+            if len(name) != 2 or name[1] not in DirectReplacement.FUNCTIONS:
+                return binop_node
+            func_name = name[1]
+
+            replacement_rule = DirectReplacement.FUNCTIONS[func_name]
+            if isinstance(replacement_rule, DirectReplacement.Transformation):
+
+                # FIXME: we do not have line number in binop?
+                binop_node.rval, input_type = replacement_rule.function(node, self.scope_vars, 0) #binop_node.line)
+                print(binop_node, binop_node.lval, binop_node.rval)
+
+                # replace types of return variable - LHS of the binary operator
+                var = binop_node.lval
+                if isinstance(var.name, ast_internal_classes.Name_Node):
+                    name = var.name.name
+                else:
+                    name = var.name
+                var_decl = self.scope_vars.get_var(var.parent, name)
+                var.type = input_type
+                var_decl.type = input_type
+
+            return binop_node
+
+
+            #self.scope_vars.get_var(node.parent, arg.name).
+
+    def replace_size(var: ast_internal_classes.Call_Expr_Node, scope_vars: ScopeVarsDeclarations, line):
+
+        if len(var.args) not in [1, 2]:
+            raise RuntimeError()
+
+        # get variable declaration for the first argument
+        var_decl = scope_vars.get_var(var.parent, var.args[0].name)
+
+        # one arg to SIZE? compute the total number of elements
+        if len(var.args) == 1:
+
+            if len(var_decl.sizes) == 1:
+                return (var_decl.sizes[0], "INTEGER")
+
+            ret = ast_internal_classes.BinOp_Node(
+                lval=var_decl.sizes[0],
+                rval=None,
+                op="*"
+            )
+            cur_node = ret
+            for i in range(1, len(var_decl.sizes) - 1):
+
+                cur_node.rval = ast_internal_classes.BinOp_Node(
+                    lval=var_decl.sizes[i],
+                    rval=None,
+                    op="*"
+                )
+                cur_node = cur_node.rval
+
+            cur_node.rval = var_decl.sizes[-1]
+            return (ret, "INTEGER")
+
+        # two arguments? We return number of elements in a given rank
+        rank = var.args[1]
+        # we do not support symbolic argument to DIM - it must be a literal
+        if not isinstance(rank, ast_internal_classes.Int_Literal_Node):
+            raise NotImplementedError()
+        value = int(rank.value)
+        return (var_decl.sizes[value-1], "INTEGER")
+
+
+    def replace_bit_size(var: ast_internal_classes.Call_Expr_Node, scope_vars: ScopeVarsDeclarations, line):
+
+        if len(var.args) != 1:
+            raise RuntimeError()
+
+        # get variable declaration for the first argument
+        var_decl = scope_vars.get_var(var.parent, var.args[0].name)
+
+        dace_type = fortrantypes2dacetypes[var_decl.type]
+        type_size = dace_type().itemsize * 8
+
+        return (ast_internal_classes.Int_Literal_Node(value=str(type_size)), "INTEGER")
+
+
+    def replace_int_kind(args: ast_internal_classes.Arg_List_Node, line):
+        return ast_internal_classes.Int_Literal_Node(value=str(
+            math.ceil((math.log2(math.pow(10, int(args.args[0].value))) + 1) / 8)),
+                                                        line_number=line)
+
+    def replace_real_kind(args: ast_internal_classes.Arg_List_Node, line):
+        if int(args.args[0].value) >= 9 or int(args.args[1].value) > 126:
+            return ast_internal_classes.Int_Literal_Node(value="8", line_number=line)
+        elif int(args.args[0].value) >= 3 or int(args.args[1].value) > 14:
+            return ast_internal_classes.Int_Literal_Node(value="4", line_number=line)
+        else:
+            return ast_internal_classes.Int_Literal_Node(value="2", line_number=line)
+
 
     FUNCTIONS = {
-        "SELECTED_INT_KIND": "__dace_selected_int_kind",
-        "SELECTED_REAL_KIND": "__dace_selected_real_kind",
+        "SELECTED_INT_KIND": Replacement(replace_int_kind),
+        "SELECTED_REAL_KIND": Replacement(replace_real_kind),
+        "BIT_SIZE": Transformation(replace_bit_size),
+        "SIZE": Transformation(replace_size)
     }
 
     @staticmethod
-    def replaced_name(func_name: str) -> str:
-        return SelectedKind.FUNCTIONS[func_name]
+    def temporary_functions():
+
+        # temporary functions created by us -> f becomes __dace_f
+        # We provide this to tell Fortran parser that these are function calls,
+        # not array accesses
+        funcs = list(DirectReplacement.FUNCTIONS.keys())
+        return [f'__dace_{f}' for f in funcs]
+
+    @staticmethod
+    def replacable_name(func_name: str) -> bool:
+        return func_name in DirectReplacement.FUNCTIONS
+
+    @staticmethod
+    def replace_name(func_name: str) -> str:
+        #return ast_internal_classes.Name_Node(name=DirectReplacement.FUNCTIONS[func_name][0])
+        return ast_internal_classes.Name_Node(name=f'__dace_{func_name}')
+
+    @staticmethod
+    def replacable(func_name: str) -> bool:
+        orig_name = func_name.split('__dace_')
+        if len(orig_name) > 1 and orig_name[1] in DirectReplacement.FUNCTIONS:
+            return isinstance(DirectReplacement.FUNCTIONS[orig_name[1]], DirectReplacement.Replacement)
+        return False
 
     @staticmethod
     def replace(func_name: ast_internal_classes.Name_Node, args: ast_internal_classes.Arg_List_Node, line) -> ast_internal_classes.FNode:
 
-        if func_name.name == "__dace_selected_int_kind":
-            return ast_internal_classes.Int_Literal_Node(value=str(
-                math.ceil((math.log2(math.pow(10, int(args.args[0].value))) + 1) / 8)),
-                                                         line_number=line)
-        # This selects the smallest kind that can hold the given number of digits (fp64,fp32 or fp16)
-        elif func_name.name == "__dace_selected_real_kind":
-            if int(args.args[0].value) >= 9 or int(args.args[1].value) > 126:
-                return ast_internal_classes.Int_Literal_Node(value="8", line_number=line)
-            elif int(args.args[0].value) >= 3 or int(args.args[1].value) > 14:
-                return ast_internal_classes.Int_Literal_Node(value="4", line_number=line)
-            else:
-                return ast_internal_classes.Int_Literal_Node(value="2", line_number=line)
+        # Here we already have __dace_func
+        fname = func_name.split('__dace_')[1]
+        return DirectReplacement.FUNCTIONS[fname].function(args, line)
 
-        raise NotImplemented()
+    def has_transformation(fname: str) -> bool:
+        return isinstance(DirectReplacement.FUNCTIONS[fname], DirectReplacement.Transformation)
+
+    @staticmethod
+    def get_transformation() -> IntrinsicNodeTransformer:
+        return DirectReplacement.ASTTransformation()
 
 class LoopBasedReplacement:
 
@@ -84,36 +226,34 @@ class LoopBasedReplacementVisitor(NodeVisitor):
     def __init__(self, func_name: str):
         self._func_name = func_name
         self.nodes: List[ast_internal_classes.FNode] = []
+        self.calls: List[ast_internal_classes.FNode] = []
 
     def visit_BinOp_Node(self, node: ast_internal_classes.BinOp_Node):
-
         if isinstance(node.rval, ast_internal_classes.Call_Expr_Node):
             if node.rval.name.name == self._func_name:
                 self.nodes.append(node)
+                self.calls.append(node.rval)
+        self.visit(node.lval)
+        self.visit(node.rval)
+
+    def visit_Call_Expr_Node(self, node: ast_internal_classes.Call_Expr_Node):
+
+        if node.name.name == self._func_name:
+            if node not in self.calls:
+                self.nodes.append(node)
 
     def visit_Execution_Part_Node(self, node: ast_internal_classes.Execution_Part_Node):
         return
 
-class LoopBasedReplacementTransformation(NodeTransformer):
+class LoopBasedReplacementTransformation(IntrinsicNodeTransformer):
 
     """
     Transforms the AST by removing intrinsic call and replacing it with loops
     """
-    def __init__(self, ast):
+    def __init__(self):
         self.count = 0
-
-        # We need to rerun the assignment because transformations could have created
-        # new AST nodes
-        ParentScopeAssigner().visit(ast)
-        self.scope_vars = ScopeVarsDeclarations()
-        self.scope_vars.visit(ast)
         self.rvals = []
 
-    @staticmethod
-    @abstractmethod
-    def func_name() -> str:
-        pass
-
     @abstractmethod
     def _initialize(self):
         pass
@@ -338,9 +478,6 @@ def visit_Execution_Part_Node(self, node: ast_internal_classes.Execution_Part_No
 
 class SumProduct(LoopBasedReplacementTransformation):
 
-    def __init__(self, ast):
-        super().__init__(ast)
-
     def _initialize(self):
         self.rvals = []
         self.argument_variable = None
@@ -414,9 +551,6 @@ class Sum(LoopBasedReplacement):
 
     class Transformation(SumProduct):
 
-        def __init__(self, ast):
-            super().__init__(ast)
-
         @staticmethod
         def func_name() -> str:
             return "__dace_sum"
@@ -440,9 +574,6 @@ class Product(LoopBasedReplacement):
 
     class Transformation(SumProduct):
 
-        def __init__(self, ast):
-            super().__init__(ast)
-
         @staticmethod
         def func_name() -> str:
             return "__dace_product"
@@ -455,9 +586,6 @@ def _result_update_op(self):
 
 class AnyAllCountTransformation(LoopBasedReplacementTransformation):
 
-    def __init__(self, ast):
-        super().__init__(ast)
-
     def _initialize(self):
         self.rvals = []
 
@@ -575,9 +703,6 @@ class Any(LoopBasedReplacement):
     """
     class Transformation(AnyAllCountTransformation):
 
-        def __init__(self, ast):
-            super().__init__(ast)
-
         def _result_init_value(self):
             return "0"
 
@@ -607,9 +732,6 @@ class All(LoopBasedReplacement):
     """
     class Transformation(AnyAllCountTransformation):
 
-        def __init__(self, ast):
-            super().__init__(ast)
-
         def _result_init_value(self):
             return "1"
 
@@ -644,9 +766,6 @@ class Count(LoopBasedReplacement):
     """
     class Transformation(AnyAllCountTransformation):
 
-        def __init__(self, ast):
-            super().__init__(ast)
-
         def _result_init_value(self):
             return "0"
 
@@ -675,9 +794,6 @@ def func_name() -> str:
 
 class MinMaxValTransformation(LoopBasedReplacementTransformation):
 
-    def __init__(self, ast):
-        super().__init__(ast)
-
     def _initialize(self):
         self.rvals = []
         self.argument_variable = None
@@ -753,9 +869,6 @@ class MinVal(LoopBasedReplacement):
     """
     class Transformation(MinMaxValTransformation):
 
-        def __init__(self, ast):
-            super().__init__(ast)
-
         def _result_init_value(self, array: ast_internal_classes.Array_Subscript_Node):
 
             var_decl = self.scope_vars.get_var(array.parent, array.name.name)
@@ -788,9 +901,6 @@ class MaxVal(LoopBasedReplacement):
     """
     class Transformation(MinMaxValTransformation):
 
-        def __init__(self, ast):
-            super().__init__(ast)
-
         def _result_init_value(self, array: ast_internal_classes.Array_Subscript_Node):
 
             var_decl = self.scope_vars.get_var(array.parent, array.name.name)
@@ -817,9 +927,6 @@ class Merge(LoopBasedReplacement):
 
     class Transformation(LoopBasedReplacementTransformation):
 
-        def __init__(self, ast):
-            super().__init__(ast)
-
         def _initialize(self):
             self.rvals = []
 
@@ -939,11 +1046,235 @@ def _generate_loop_body(self, node: ast_internal_classes.FNode) -> ast_internal_
                 line_number=node.line_number
             )
 
+class MathFunctions(IntrinsicTransformation):
+
+    MathTransformation = namedtuple("MathTransformation", "function return_type")
+    MathReplacement = namedtuple("MathReplacement", "function replacement_function return_type")
+
+    def generate_scale(arg: ast_internal_classes.Call_Expr_Node):
+
+        # SCALE(X, I) becomes: X * pow(RADIX(X), I)
+        # In our case, RADIX(X) is always 2
+        line = arg.line_number
+        x = arg.args[0]
+        i = arg.args[1]
+        const_two = ast_internal_classes.Int_Literal_Node(value="2")
+
+        # I and RADIX(X) are both integers
+        rval = ast_internal_classes.Call_Expr_Node(
+            name=ast_internal_classes.Name_Node(name="pow"),
+            type="INTEGER",
+            args=[const_two, i],
+            line_number=line
+        )
+
+        mult = ast_internal_classes.BinOp_Node(
+            op="*",
+            lval=x,
+            rval=rval,
+            line_number=line
+        )
+
+        # pack it into parentheses, just to be sure
+        return ast_internal_classes.Parenthesis_Expr_Node(expr=mult)
+
+    def generate_aint(arg: ast_internal_classes.Call_Expr_Node):
+
+        # The call to AINT can contain a second KIND parameter
+        # We ignore it a the moment.
+        # However, to map into C's trunc, we need to drop it.
+        if len(arg.args) > 1:
+            del arg.args[1]
+
+        fname = arg.name.name.split('__dace_')[1]
+        if fname in "AINT":
+            arg.name = ast_internal_classes.Name_Node(name="trunc")
+        elif fname == "NINT":
+            arg.name = ast_internal_classes.Name_Node(name="iround")
+        elif fname == "ANINT":
+            arg.name = ast_internal_classes.Name_Node(name="round")
+        else:
+            raise NotImplementedError()
+
+        return arg
+
+    INTRINSIC_TO_DACE = {
+        "MIN": MathTransformation("min", "FIRST_ARG"),
+        "MAX": MathTransformation("max", "FIRST_ARG"),
+        "SQRT": MathTransformation("sqrt", "FIRST_ARG"),
+        "ABS": MathTransformation("abs", "FIRST_ARG"),
+        "EXP": MathTransformation("exp", "FIRST_ARG"),
+        # Documentation states that the return type of LOG is always REAL,
+        # but the kind is the same as of the first argument.
+        # However, we already replaced kind with types used in DaCe.
+        # Thus, a REAL that is really DOUBLE will be double in the first argument.
+        "LOG": MathTransformation("log", "FIRST_ARG"),
+        "MOD": {
+            "INTEGER": MathTransformation("Mod", "INTEGER"),
+            "REAL": MathTransformation("Mod_float", "REAL"),
+            "DOUBLE": MathTransformation("Mod_float", "DOUBLE")
+        },
+        "MODULO": {
+            "INTEGER": MathTransformation("Modulo", "INTEGER"),
+            "REAL": MathTransformation("Modulo_float", "REAL"),
+            "DOUBLE": MathTransformation("Modulo_float", "DOUBLE")
+        },
+        "FLOOR": {
+            "REAL": MathTransformation("floor", "INTEGER"),
+            "DOUBLE": MathTransformation("floor", "INTEGER")
+        },
+        "SCALE": MathReplacement(None, generate_scale, "FIRST_ARG"),
+        "EXPONENT": MathTransformation("frexp", "INTEGER"),
+        "INT": MathTransformation("int", "INTEGER"),
+        "AINT": MathReplacement("trunc", generate_aint, "FIRST_ARG"),
+        "NINT": MathReplacement("iround", generate_aint, "INTEGER"),
+        "ANINT": MathReplacement("round", generate_aint, "FIRST_ARG"),
+        "REAL": MathTransformation("float", "REAL"),
+        "DBLE": MathTransformation("double", "DOUBLE"),
+        "SIN": MathTransformation("sin", "FIRST_ARG"),
+        "COS": MathTransformation("cos", "FIRST_ARG"),
+        "SINH": MathTransformation("sinh", "FIRST_ARG"),
+        "COSH": MathTransformation("cosh", "FIRST_ARG"),
+        "TANH": MathTransformation("tanh", "FIRST_ARG"),
+        "ASIN": MathTransformation("asin", "FIRST_ARG"),
+        "ACOS": MathTransformation("acos", "FIRST_ARG"),
+        "ATAN": MathTransformation("atan", "FIRST_ARG"),
+        "ATAN2": MathTransformation("atan2", "FIRST_ARG")
+    }
+
+    class TypeTransformer(IntrinsicNodeTransformer):
+
+        def func_type(self, node: ast_internal_classes.Call_Expr_Node):
+
+            # take the first arg
+            arg = node.args[0]
+            if isinstance(arg, ast_internal_classes.Real_Literal_Node):
+                return 'REAL'
+            elif isinstance(arg, ast_internal_classes.Int_Literal_Node):
+                return 'INTEGER'
+            elif isinstance(arg, ast_internal_classes.Call_Expr_Node):
+                return arg.type
+            elif isinstance(arg, ast_internal_classes.Name_Node):
+                input_type = self.scope_vars.get_var(node.parent, arg.name)
+                return input_type.type
+            else:
+                input_type = self.scope_vars.get_var(node.parent, arg.name.name)
+                return input_type.type
+
+        def replace_call(self, old_call: ast_internal_classes.Call_Expr_Node, new_call: ast_internal_classes.FNode):
+
+            parent = old_call.parent
+
+            # We won't need it if the CallExtractor will properly support nested function calls.
+            # Then, all function calls should be a binary op: val = func()
+            if isinstance(parent, ast_internal_classes.BinOp_Node):
+                if parent.lval == old_call:
+                    parent.lval = new_call
+                else:
+                    parent.rval = new_call
+            elif isinstance(parent, ast_internal_classes.UnOp_Node):
+                parent.lval = new_call
+            elif isinstance(parent, ast_internal_classes.Parenthesis_Expr_Node):
+                parent.expr = new_call
+            elif isinstance(parent, ast_internal_classes.Call_Expr_Node):
+                for idx, arg in enumerate(parent.args):
+                    if arg == old_call:
+                        parent.args[idx] = new_call
+                        break
+            else:
+                raise NotImplementedError()
+
+        def visit_BinOp_Node(self, binop_node: ast_internal_classes.BinOp_Node):
+
+            if not isinstance(binop_node.rval, ast_internal_classes.Call_Expr_Node):
+                return binop_node
+
+            node = binop_node.rval
+
+            name = node.name.name.split('__dace_')
+            if len(name) != 2 or name[1] not in MathFunctions.INTRINSIC_TO_DACE:
+                return binop_node
+            func_name = name[1]
+
+            # Visit all children before we expand this call.
+            # We need that to properly get the type.
+            for arg in node.args:
+                self.visit(arg)
+
+            return_type = None
+            input_type = None
+            input_type = self.func_type(node)
+
+            replacement_rule = MathFunctions.INTRINSIC_TO_DACE[func_name]
+            if isinstance(replacement_rule, dict):
+                replacement_rule = replacement_rule[input_type]
+            if replacement_rule.return_type == "FIRST_ARG":
+                return_type = input_type
+            else:
+                return_type = replacement_rule.return_type
+
+            if isinstance(replacement_rule, MathFunctions.MathTransformation):
+                node.name = ast_internal_classes.Name_Node(name=replacement_rule.function)
+                node.type = return_type
+
+            else:
+                binop_node.rval = replacement_rule.replacement_function(node)
+
+            # replace types of return variable - LHS of the binary operator
+            var = binop_node.lval
+            name = None
+            if isinstance(var.name, ast_internal_classes.Name_Node):
+                name = var.name.name
+            else:
+                name = var.name
+            var_decl = self.scope_vars.get_var(var.parent, name)
+            var.type = input_type
+            var_decl.type = input_type
+
+            return binop_node
+
+    @staticmethod
+    def dace_functions():
+
+        # list of final dace functions which we create
+        funcs = list(MathFunctions.INTRINSIC_TO_DACE.values())
+        res = []
+        # flatten nested lists
+        for f in funcs:
+            if isinstance(f, dict):
+                res.extend([v.function for k, v in f.items() if v.function is not None])
+            else:
+                if f.function is not None:
+                    res.append(f.function)
+        return res
+
+    @staticmethod
+    def temporary_functions():
+
+        # temporary functions created by us -> f becomes __dace_f
+        # We provide this to tell Fortran parser that these are function calls,
+        # not array accesses
+        funcs = list(MathFunctions.INTRINSIC_TO_DACE.keys())
+        return [f'__dace_{f}' for f in funcs]
+
+    @staticmethod
+    def replacable(func_name: str) -> bool:
+        return func_name in MathFunctions.INTRINSIC_TO_DACE
+
+    @staticmethod
+    def replace(func_name: str) -> ast_internal_classes.FNode:
+        return ast_internal_classes.Name_Node(name=f'__dace_{func_name}')
+
+    def has_transformation() -> bool:
+        return True
+
+    @staticmethod
+    def get_transformation() -> TypeTransformer:
+        return MathFunctions.TypeTransformer()
+
 class FortranIntrinsics:
 
     IMPLEMENTATIONS_AST = {
-        "SELECTED_INT_KIND": SelectedKind,
-        "SELECTED_REAL_KIND": SelectedKind,
         "SUM": Sum,
         "PRODUCT": Product,
         "ANY": Any,
@@ -954,11 +1285,6 @@ class FortranIntrinsics:
         "MERGE": Merge
     }
 
-    DIRECT_REPLACEMENTS = {
-        "__dace_selected_int_kind": SelectedKind,
-        "__dace_selected_real_kind": SelectedKind
-    }
-
     EXEMPTED_FROM_CALL_EXTRACTION = [
         Merge
     ]
@@ -971,59 +1297,58 @@ def transformations(self) -> Set[Type[NodeTransformer]]:
 
     @staticmethod
     def function_names() -> List[str]:
-        return list(LoopBasedReplacement.INTRINSIC_TO_DACE.values())
+        # list of all functions that are created by initial transformation, before doing full replacement
+        # this prevents other parser components from replacing our function calls with array subscription nodes
+        return [*list(LoopBasedReplacement.INTRINSIC_TO_DACE.values()), *MathFunctions.temporary_functions(), *DirectReplacement.temporary_functions()]
+
+    @staticmethod
+    def retained_function_names() -> List[str]:
+        # list of all DaCe functions that we use after full parsing
+        return MathFunctions.dace_functions()
 
     @staticmethod
     def call_extraction_exemptions() -> List[str]:
-        return [func.Transformation.func_name() for func in FortranIntrinsics.EXEMPTED_FROM_CALL_EXTRACTION]
+        return [
+            *[func.Transformation.func_name() for func in FortranIntrinsics.EXEMPTED_FROM_CALL_EXTRACTION]
+            #*MathFunctions.temporary_functions()
+        ]
 
     def replace_function_name(self, node: FASTNode) -> ast_internal_classes.Name_Node:
 
         func_name = node.string
         replacements = {
-            "INT": "__dace_int",
-            "DBLE": "__dace_dble",
-            "SQRT": "sqrt",
-            "COSH": "cosh",
-            "ABS": "abs",
-            "MIN": "min",
-            "MAX": "max",
-            "EXP": "exp",
-            "EPSILON": "__dace_epsilon",
-            "TANH": "tanh",
             "SIGN": "__dace_sign",
-            "EXP": "exp"
         }
         if func_name in replacements:
             return ast_internal_classes.Name_Node(name=replacements[func_name])
-        else:
-
-            if self.IMPLEMENTATIONS_AST[func_name].has_transformation():
-                self._transformations_to_run.add(self.IMPLEMENTATIONS_AST[func_name].Transformation)
+        elif DirectReplacement.replacable_name(func_name):
+            if DirectReplacement.has_transformation(func_name):
+                self._transformations_to_run.add(DirectReplacement.get_transformation())
+            return DirectReplacement.replace_name(func_name)
+        elif MathFunctions.replacable(func_name):
+            self._transformations_to_run.add(MathFunctions.get_transformation())
+            return MathFunctions.replace(func_name)
+
+        if self.IMPLEMENTATIONS_AST[func_name].has_transformation():
+
+            if hasattr(self.IMPLEMENTATIONS_AST[func_name], "Transformation"):
+                self._transformations_to_run.add(self.IMPLEMENTATIONS_AST[func_name].Transformation())
+            else:
+                self._transformations_to_run.add(self.IMPLEMENTATIONS_AST[func_name].get_transformation(func_name))
 
-            return ast_internal_classes.Name_Node(name=self.IMPLEMENTATIONS_AST[func_name].replaced_name(func_name))
+        return ast_internal_classes.Name_Node(name=self.IMPLEMENTATIONS_AST[func_name].replaced_name(func_name))
 
     def replace_function_reference(self, name: ast_internal_classes.Name_Node, args: ast_internal_classes.Arg_List_Node, line):
 
         func_types = {
-            "__dace_int": "INT",
-            "__dace_dble": "DOUBLE",
-            "sqrt": "DOUBLE",
-            "cosh": "DOUBLE",
-            "abs": "DOUBLE",
-            "min": "DOUBLE",
-            "max": "DOUBLE",
-            "exp": "DOUBLE",
-            "__dace_epsilon": "DOUBLE",
-            "tanh": "DOUBLE",
             "__dace_sign": "DOUBLE",
         }
         if name.name in func_types:
             # FIXME: this will be progressively removed
             call_type = func_types[name.name]
             return ast_internal_classes.Call_Expr_Node(name=name, type=call_type, args=args.args, line_number=line)
-        elif name.name in self.DIRECT_REPLACEMENTS:
-            return self.DIRECT_REPLACEMENTS[name.name].replace(name, args, line)
+        elif DirectReplacement.replacable(name.name):
+            return DirectReplacement.replace(name.name, args, line)
         else:
             # We will do the actual type replacement later
             # To that end, we need to know the input types - but these we do not know at the moment.
diff --git a/dace/runtime/include/dace/math.h b/dace/runtime/include/dace/math.h
index 0a9d153767..4dae494a8a 100644
--- a/dace/runtime/include/dace/math.h
+++ b/dace/runtime/include/dace/math.h
@@ -61,6 +61,45 @@ static DACE_CONSTEXPR DACE_HDFI T Mod(const T& value, const T2& modulus) {
     return value % modulus;
 }
 
+// Fortran implements MOD for floating-point values as well
+template <typename T>
+static DACE_CONSTEXPR DACE_HDFI T Mod_float(const T& value, const T& modulus) {
+    return value - static_cast<int>(value / modulus) * modulus;
+}
+
+// Fortran implementation of MODULO
+template <typename T>
+static DACE_CONSTEXPR DACE_HDFI T Modulo(const T& value, const T& modulus) {
+    // Fortran implementation for integers - find R such that value = Q * modulus + R
+    // However, R must be in [0, modulus)
+    // To achieve that, we need to cast the division to floats.
+    // Example: -17, 3 must produce 1 and not -2.
+    // If we don't use cast, the floor is called on -5, producing wrong value.
+    // Instead, we need to have floor(-5.6... ) to ensure it produces -6.
+    // Similarly, 17, -3 must produce -1 and not 2.
+    // This means that the default solution works if value and modulus have the same sign.
+    return value - floor(static_cast<float>(value) / modulus) * modulus;
+}
+
+template <typename T>
+static DACE_CONSTEXPR DACE_HDFI T Modulo_float(const T& value, const T& modulus) {
+    return value - floor(value / modulus) * modulus;
+}
+
+// Implement to support a match wtih Fortran's intrinsic EXPONENT
+template<typename T, std::enable_if_t<std::is_floating_point<T>::value>* = nullptr>
+static DACE_CONSTEXPR DACE_HDFI int frexp(const T& a) {
+  int exponent = 0;
+  std::frexp(a, &exponent);
+  return exponent;
+}
+
+// Implement to support Fortran's intrinsic NINT - round, but return an integer
+template<typename T, std::enable_if_t<std::is_floating_point<T>::value>* = nullptr>
+static DACE_CONSTEXPR DACE_HDFI int iround(const T& a) {
+  return static_cast<int>(round(a));
+}
+
 template <typename T, typename T2>
 static DACE_CONSTEXPR DACE_HDFI T int_ceil(const T& numerator, const T2& denominator) {
     return (numerator + denominator - 1) / denominator;
diff --git a/tests/fortran/call_extract_test.py b/tests/fortran/call_extract_test.py
new file mode 100644
index 0000000000..eb1f2ac86d
--- /dev/null
+++ b/tests/fortran/call_extract_test.py
@@ -0,0 +1,39 @@
+# Copyright 2019-2023 ETH Zurich and the DaCe authors. All rights reserved.
+
+import numpy as np
+import pytest
+
+from dace.frontend.fortran import fortran_parser
+
+def test_fortran_frontend_call_extract():
+    test_string = """
+                    PROGRAM intrinsic_call_extract
+                    implicit none
+                    real, dimension(2) :: d
+                    real, dimension(2) :: res
+                    CALL intrinsic_call_extract_test_function(d,res)
+                    end
+
+                    SUBROUTINE intrinsic_call_extract_test_function(d,res)
+                    real, dimension(2) :: d
+                    real, dimension(2) :: res
+
+                    res(1) = SQRT(SIGN(EXP(d(1)), LOG(d(1))))
+                    res(2) = MIN(SQRT(EXP(d(1))), SQRT(EXP(d(1))) - 1)
+
+                    END SUBROUTINE intrinsic_call_extract_test_function
+                    """
+
+    sdfg = fortran_parser.create_sdfg_from_string(test_string, "intrinsic_call_extract", False)
+    sdfg.simplify(verbose=True)
+    sdfg.compile()
+
+    input = np.full([2], 42, order="F", dtype=np.float32)
+    res = np.full([2], 42, order="F", dtype=np.float32)
+    sdfg(d=input, res=res)
+    assert np.allclose(res, [np.sqrt(np.exp(input[0])), np.sqrt(np.exp(input[0])) - 1])
+
+
+if __name__ == "__main__":
+
+    test_fortran_frontend_call_extract()
diff --git a/tests/fortran/intrinsic_basic_test.py b/tests/fortran/intrinsic_basic_test.py
new file mode 100644
index 0000000000..9ef31dd108
--- /dev/null
+++ b/tests/fortran/intrinsic_basic_test.py
@@ -0,0 +1,98 @@
+# Copyright 2019-2023 ETH Zurich and the DaCe authors. All rights reserved.
+
+import numpy as np
+import pytest
+
+from dace.frontend.fortran import fortran_parser
+
+def test_fortran_frontend_bit_size():
+    test_string = """
+                    PROGRAM intrinsic_math_test_bit_size
+                    implicit none
+                    integer, dimension(4) :: res
+                    CALL intrinsic_math_test_function(res)
+                    end
+
+                    SUBROUTINE intrinsic_math_test_function(res)
+                    integer, dimension(4) :: res
+                    logical :: a = .TRUE.
+                    integer :: b = 1
+                    real :: c = 1
+                    double precision :: d = 1
+
+                    res(1) = BIT_SIZE(a)
+                    res(2) = BIT_SIZE(b)
+                    res(3) = BIT_SIZE(c)
+                    res(4) = BIT_SIZE(d)
+
+                    END SUBROUTINE intrinsic_math_test_function
+                    """
+
+    sdfg = fortran_parser.create_sdfg_from_string(test_string, "intrinsic_math_test_bit_size", False)
+    sdfg.simplify(verbose=True)
+    sdfg.compile()
+
+    size = 4
+    res = np.full([size], 42, order="F", dtype=np.int32)
+    sdfg(res=res)
+
+    assert np.allclose(res, [32, 32, 32, 64])
+
+def test_fortran_frontend_bit_size_symbolic():
+    test_string = """
+                    PROGRAM intrinsic_math_test_bit_size
+                    implicit none
+                    integer, parameter :: arrsize = 2
+                    integer, parameter :: arrsize2 = 3
+                    integer, parameter :: arrsize3 = 4
+                    integer :: res(arrsize)
+                    integer :: res2(arrsize, arrsize2, arrsize3)
+                    integer :: res3(arrsize+arrsize2, arrsize2 * 5, arrsize3 + arrsize2*arrsize)
+                    CALL intrinsic_math_test_function(arrsize, arrsize2, arrsize3, res, res2, res3)
+                    end
+
+                    SUBROUTINE intrinsic_math_test_function(arrsize, arrsize2, arrsize3, res, res2, res3)
+                    implicit none
+                    integer :: arrsize
+                    integer :: arrsize2
+                    integer :: arrsize3
+                    integer :: res(arrsize)
+                    integer :: res2(arrsize, arrsize2, arrsize3)
+                    integer :: res3(arrsize+arrsize2, arrsize2 * 5, arrsize3 + arrsize2*arrsize)
+
+                    res(1) = SIZE(res)
+                    res(2) = SIZE(res2)
+                    res(3) = SIZE(res3)
+                    res(4) = SIZE(res)*2
+                    res(5) = SIZE(res)*SIZE(res2)*SIZE(res3)
+                    res(6) = SIZE(res2, 1) + SIZE(res2, 2) + SIZE(res2, 3)
+                    res(7) = SIZE(res3, 1) + SIZE(res3, 2) + SIZE(res3, 3)
+
+                    END SUBROUTINE intrinsic_math_test_function
+                    """
+
+    sdfg = fortran_parser.create_sdfg_from_string(test_string, "intrinsic_math_test_bit_size", False)
+    sdfg.simplify(verbose=True)
+    sdfg.compile()
+
+    size = 24
+    size2 = 5
+    size3 = 7
+    res = np.full([size], 42, order="F", dtype=np.int32)
+    res2 = np.full([size, size2, size3], 42, order="F", dtype=np.int32)
+    res3 = np.full([size+size2, size2*5, size3 + size*size2], 42, order="F", dtype=np.int32)
+    sdfg(res=res, res2=res2, res3=res3, arrsize=size, arrsize2=size2, arrsize3=size3)
+    print(res)
+
+    assert res[0] == size
+    assert res[1] == size*size2*size3
+    assert res[2] == (size + size2) * (size2 * 5) * (size3 + size2*size)
+    assert res[3] == size * 2 
+    assert res[4] == res[0] * res[1] * res[2]
+    assert res[5] == size + size2 + size3
+    assert res[6] == size + size2 + size2*5 + size3 + size*size2
+
+
+if __name__ == "__main__":
+    test_fortran_frontend_bit_size()
+    test_fortran_frontend_bit_size_symbolic()
diff --git a/tests/fortran/intrinsic_math_test.py b/tests/fortran/intrinsic_math_test.py
new file mode 100644
index 0000000000..e1fc469beb
--- /dev/null
+++ b/tests/fortran/intrinsic_math_test.py
@@ -0,0 +1,845 @@
+# Copyright 2019-2023 ETH Zurich and the DaCe authors. All rights reserved.
+
+import numpy as np
+import pytest
+
+from dace.frontend.fortran import fortran_parser
+
+def test_fortran_frontend_min_max():
+    test_string = """
+                    PROGRAM intrinsic_math_test_min_max
+                    implicit none
+                    double precision, dimension(2) :: arg1
+                    double precision, dimension(2) :: arg2
+                    double precision, dimension(2) :: res1
+                    double precision, dimension(2) :: res2
+                    CALL intrinsic_math_test_function(arg1, arg2, res1, res2)
+                    end
+
+                    SUBROUTINE intrinsic_math_test_function(arg1, arg2, res1, res2)
+                    double precision, dimension(2) :: arg1
+                    double precision, dimension(2) :: arg2
+                    double precision, dimension(2) :: res1
+                    double precision, dimension(2) :: res2
+
+                    res1(1) = MIN(arg1(1), arg2(1))
+                    res1(2) = MIN(arg1(2), arg2(2))
+
+                    res2(1) = MAX(arg1(1), arg2(1))
+                    res2(2) = MAX(arg1(2), arg2(2))
+
+                    END SUBROUTINE intrinsic_math_test_function
+                    """
+
+    sdfg = fortran_parser.create_sdfg_from_string(test_string, "intrinsic_math_test_min_max", False)
+    sdfg.simplify(verbose=True)
+    sdfg.compile()
+
+    size = 2
+    arg1 = np.full([size], 42, order="F", dtype=np.float64)
+    arg2 = np.full([size], 42, order="F", dtype=np.float64)
+
+    arg1[0] = 20
+    arg1[1] = 25
+    arg2[0] = 30
+    arg2[1] = 18
+
+    res1 = np.full([2], 42, order="F", dtype=np.float64)
+    res2 = np.full([2], 42, order="F", dtype=np.float64)
+    sdfg(arg1=arg1, arg2=arg2, res1=res1, res2=res2)
+
+    assert res1[0] == 20
+    assert res1[1] == 18
+    assert res2[0] == 30
+    assert res2[1] == 25
+
+
+def test_fortran_frontend_sqrt():
+    test_string = """
+                    PROGRAM intrinsic_math_test_sqrt
+                    implicit none
+                    double precision, dimension(2) :: d
+                    double precision, dimension(2) :: res
+                    CALL intrinsic_math_test_function(d, res)
+                    end
+
+                    SUBROUTINE intrinsic_math_test_function(d, res)
+                    double precision, dimension(2) :: d
+                    double precision, dimension(2) :: res
+
+                    res(1) = SQRT(d(1))
+                    res(2) = SQRT(d(2))
+
+                    END SUBROUTINE intrinsic_math_test_function
+                    """
+
+    sdfg = fortran_parser.create_sdfg_from_string(test_string, "intrinsic_math_test_sqrt", False)
+    sdfg.simplify(verbose=True)
+    sdfg.compile()
+
+    size = 2
+    d = np.full([size], 42, order="F", dtype=np.float64)
+    d[0] = 2
+    d[1] = 5
+    res = np.full([2], 42, order="F", dtype=np.float64)
+    sdfg(d=d, res=res)
+    py_res = np.sqrt(d)
+
+    for f_res, p_res in zip(res, py_res):
+        assert abs(f_res - p_res) < 10**-9
+
+def test_fortran_frontend_abs():
+    test_string = """
+                    PROGRAM intrinsic_math_test_abs
+                    implicit none
+                    double precision, dimension(2) :: d
+                    double precision, dimension(2) :: res
+                    CALL intrinsic_math_test_function(d, res)
+                    end
+
+                    SUBROUTINE intrinsic_math_test_function(d, res)
+                    double precision, dimension(2) :: d
+                    double precision, dimension(2) :: res
+
+                    res(1) = ABS(d(1))
+                    res(2) = ABS(d(2))
+
+                    END SUBROUTINE intrinsic_math_test_function
+                    """
+
+    sdfg = fortran_parser.create_sdfg_from_string(test_string, "intrinsic_math_test_abs", False)
+    sdfg.simplify(verbose=True)
+    sdfg.compile()
+
+    size = 2
+    d = np.full([size], 42, order="F", dtype=np.float64)
+    d[0] = -30
+    d[1] = 40
+    res = np.full([2], 42, order="F", dtype=np.float64)
+    sdfg(d=d, res=res)
+
+    assert res[0] == 30
+    assert res[1] == 40
+
+def test_fortran_frontend_exp():
+    test_string = """
+                    PROGRAM intrinsic_math_test_exp
+                    implicit none
+                    double precision, dimension(2) :: d
+                    double precision, dimension(2) :: res
+                    CALL intrinsic_math_test_function(d, res)
+                    end
+
+                    SUBROUTINE intrinsic_math_test_function(d, res)
+                    double precision, dimension(2) :: d
+                    double precision, dimension(2) :: res
+
+                    res(1) = EXP(d(1))
+                    res(2) = EXP(d(2))
+
+                    END SUBROUTINE intrinsic_math_test_function
+                    """
+
+    sdfg = fortran_parser.create_sdfg_from_string(test_string, "intrinsic_math_test_exp", False)
+    sdfg.simplify(verbose=True)
+    sdfg.compile()
+
+    size = 2
+    d = np.full([size], 42, order="F", dtype=np.float64)
+    d[0] = 2
+    d[1] = 4.5
+    res = np.full([2], 42, order="F", dtype=np.float64)
+    sdfg(d=d, res=res)
+    py_res = np.exp(d)
+
+    for f_res, p_res in zip(res, py_res):
+        assert abs(f_res - p_res) < 10**-9
+
+def test_fortran_frontend_log():
+    test_string = """
+                    PROGRAM intrinsic_math_test_log
+                    implicit none
+                    double precision, dimension(2) :: d
+                    double precision, dimension(2) :: res
+                    CALL intrinsic_math_test_function(d, res)
+                    end
+
+                    SUBROUTINE intrinsic_math_test_function(d, res)
+                    double precision, dimension(2) :: d
+                    double precision, dimension(2) :: res
+
+                    res(1) = LOG(d(1))
+                    res(2) = LOG(d(2))
+
+                    END SUBROUTINE intrinsic_math_test_function
+                    """
+
+    sdfg = fortran_parser.create_sdfg_from_string(test_string, "intrinsic_math_test_exp", False)
+    sdfg.simplify(verbose=True)
+    sdfg.compile()
+
+    size = 2
+    d = np.full([size], 42, order="F", dtype=np.float64)
+    d[0] = 2.71
+    d[1] = 4.5
+    res = np.full([2], 42, order="F", dtype=np.float64)
+    sdfg(d=d, res=res)
+    py_res = np.log(d)
+
+    for f_res, p_res in zip(res, py_res):
+        assert abs(f_res - p_res) < 10**-9
+
+def test_fortran_frontend_log():
+    test_string = """
+                    PROGRAM intrinsic_math_test_log
+                    implicit none
+                    double precision, dimension(2) :: d
+                    double precision, dimension(2) :: res
+                    CALL intrinsic_math_test_function(d, res)
+                    end
+
+                    SUBROUTINE intrinsic_math_test_function(d, res)
+                    double precision, dimension(2) :: d
+                    double precision, dimension(2) :: res
+
+                    res(1) = LOG(d(1))
+                    res(2) = LOG(d(2))
+
+                    END SUBROUTINE intrinsic_math_test_function
+                    """
+
+    sdfg = fortran_parser.create_sdfg_from_string(test_string, "intrinsic_math_test_exp", False)
+    sdfg.simplify(verbose=True)
+    sdfg.compile()
+
+    size = 2
+    d = np.full([size], 42, order="F", dtype=np.float64)
+    d[0] = 2.71
+    d[1] = 4.5
+    res = np.full([2], 42, order="F", dtype=np.float64)
+    sdfg(d=d, res=res)
+    py_res = np.log(d)
+
+    for f_res, p_res in zip(res, py_res):
+        assert abs(f_res - p_res) < 10**-9
+
+def test_fortran_frontend_mod_float():
+    test_string = """
+                    PROGRAM intrinsic_math_test_mod
+                    implicit none
+                    double precision, dimension(12) :: d
+                    double precision, dimension(6) :: res
+                    CALL intrinsic_math_test_function(d, res)
+                    end
+
+                    SUBROUTINE intrinsic_math_test_function(d, res)
+                    double precision, dimension(12) :: d
+                    double precision, dimension(6) :: res
+
+                    res(1) = MOD(d(1), d(2))
+                    res(2) = MOD(d(3), d(4))
+                    res(3) = MOD(d(5), d(6))
+                    res(4) = MOD(d(7), d(8))
+                    res(5) = MOD(d(9), d(10))
+                    res(6) = MOD(d(11), d(12))
+
+                    END SUBROUTINE intrinsic_math_test_function
+                    """
+
+    sdfg = fortran_parser.create_sdfg_from_string(test_string, "intrinsic_math_test_mod", False)
+    sdfg.simplify(verbose=True)
+    sdfg.compile()
+
+    size = 12
+    d = np.full([size], 42, order="F", dtype=np.float64)
+    d[0] = 17.
+    d[1] = 3.
+    d[2] = -17.
+    d[3] = 3.
+    d[4] = 17.
+    d[5] = -3.
+    d[6] = -17.
+    d[7] = -3.
+    d[8] = 17.5
+    d[9] = 5.5
+    d[10] = -17.5
+    d[11] = 5.5
+    res = np.full([6], 42, order="F", dtype=np.float64)
+    sdfg(d=d, res=res)
+
+    assert res[0] == 2.0
+    assert res[1] == -2.0
+    assert res[2] == 2.0
+    assert res[3] == -2.0
+    assert res[4] == 1
+    assert res[5] == -1
+
+def test_fortran_frontend_mod_integer():
+    test_string = """
+                    PROGRAM intrinsic_math_test_mod
+                    implicit none
+                    integer, dimension(8) :: d
+                    integer, dimension(4) :: res
+                    CALL intrinsic_math_test_function(d, res)
+                    end
+
+                    SUBROUTINE intrinsic_math_test_function(d, res)
+                    integer, dimension(8) :: d
+                    integer, dimension(4) :: res
+
+                    res(1) = MOD(d(1), d(2))
+                    res(2) = MOD(d(3), d(4))
+                    res(3) = MOD(d(5), d(6))
+                    res(4) = MOD(d(7), d(8))
+
+                    END SUBROUTINE intrinsic_math_test_function
+                    """
+
+    sdfg = fortran_parser.create_sdfg_from_string(test_string, "intrinsic_math_test_modulo", False)
+    sdfg.simplify(verbose=True)
+    sdfg.compile()
+
+    size = 12
+    d = np.full([size], 42, order="F", dtype=np.int32)
+    d[0] = 17
+    d[1] = 3
+    d[2] = -17
+    d[3] = 3
+    d[4] = 17
+    d[5] = -3
+    d[6] = -17
+    d[7] = -3
+    res = np.full([4], 42, order="F", dtype=np.int32)
+    sdfg(d=d, res=res)
+    assert res[0] == 2
+    assert res[1] == -2
+    assert res[2] == 2
+    assert res[3] == -2
+
+def test_fortran_frontend_modulo_float():
+    test_string = """
+                    PROGRAM intrinsic_math_test_modulo
+                    implicit none
+                    double precision, dimension(12) :: d
+                    double precision, dimension(6) :: res
+                    CALL intrinsic_math_test_function(d, res)
+                    end
+
+                    SUBROUTINE intrinsic_math_test_function(d, res)
+                    double precision, dimension(12) :: d
+                    double precision, dimension(6) :: res
+
+                    res(1) = MODULO(d(1), d(2))
+                    res(2) = MODULO(d(3), d(4))
+                    res(3) = MODULO(d(5), d(6))
+                    res(4) = MODULO(d(7), d(8))
+                    res(5) = MODULO(d(9), d(10))
+                    res(6) = MODULO(d(11), d(12))
+
+                    END SUBROUTINE intrinsic_math_test_function
+                    """
+
+    sdfg = fortran_parser.create_sdfg_from_string(test_string, "intrinsic_math_test_modulo", False)
+    sdfg.simplify(verbose=True)
+    sdfg.compile()
+
+    size = 12
+    d = np.full([size], 42, order="F", dtype=np.float64)
+    d[0] = 17.
+    d[1] = 3.
+    d[2] = -17.
+    d[3] = 3.
+    d[4] = 17.
+    d[5] = -3.
+    d[6] = -17.
+    d[7] = -3.
+    d[8] = 17.5
+    d[9] = 5.5
+    d[10] = -17.5
+    d[11] = 5.5
+    res = np.full([6], 42, order="F", dtype=np.float64)
+    sdfg(d=d, res=res)
+
+    assert res[0] == 2.0
+    assert res[1] == 1.0
+    assert res[2] == -1.0
+    assert res[3] == -2.0
+    assert res[4] == 1.0
+    assert res[5] == 4.5
+
+def test_fortran_frontend_modulo_integer():
+    test_string = """
+                    PROGRAM intrinsic_math_test_modulo
+                    implicit none
+                    integer, dimension(8) :: d
+                    integer, dimension(4) :: res
+                    CALL intrinsic_math_test_function(d, res)
+                    end
+
+                    SUBROUTINE intrinsic_math_test_function(d, res)
+                    integer, dimension(8) :: d
+                    integer, dimension(4) :: res
+
+                    res(1) = MODULO(d(1), d(2))
+                    res(2) = MODULO(d(3), d(4))
+                    res(3) = MODULO(d(5), d(6))
+                    res(4) = MODULO(d(7), d(8))
+
+                    END SUBROUTINE intrinsic_math_test_function
+                    """
+
+    sdfg = fortran_parser.create_sdfg_from_string(test_string, "intrinsic_math_test_modulo", False)
+    sdfg.simplify(verbose=True)
+    sdfg.compile()
+
+    size = 12
+    d = np.full([size], 42, order="F", dtype=np.int32)
+    d[0] = 17
+    d[1] = 3
+    d[2] = -17
+    d[3] = 3
+    d[4] = 17
+    d[5] = -3
+    d[6] = -17
+    d[7] = -3
+    res = np.full([4], 42, order="F", dtype=np.int32)
+    sdfg(d=d, res=res)
+
+    assert res[0] == 2
+    assert res[1] == 1
+    assert res[2] == -1
+    assert res[3] == -2
+
+def test_fortran_frontend_floor():
+    test_string = """
+                    PROGRAM intrinsic_math_test_floor
+                    implicit none
+                    real, dimension(4) :: d
+                    integer, dimension(4) :: res
+                    CALL intrinsic_math_test_function(d, res)
+                    end
+
+                    SUBROUTINE intrinsic_math_test_function(d, res)
+                    real, dimension(4) :: d
+                    integer, dimension(4) :: res
+
+                    res(1) = FLOOR(d(1))
+                    res(2) = FLOOR(d(2))
+                    res(3) = FLOOR(d(3))
+                    res(4) = FLOOR(d(4))
+
+                    END SUBROUTINE intrinsic_math_test_function
+                    """
+
+    sdfg = fortran_parser.create_sdfg_from_string(test_string, "intrinsic_math_test_modulo", False)
+    sdfg.simplify(verbose=True)
+    sdfg.compile()
+
+    size = 4
+    d = np.full([size], 42, order="F", dtype=np.float32)
+    d[0] = 3.5
+    d[1] = 63.000001
+    d[2] = -3.5
+    d[3] = -63.00001
+    res = np.full([4], 42, order="F", dtype=np.int32)
+    sdfg(d=d, res=res)
+
+    assert res[0] == 3
+    assert res[1] == 63
+    assert res[2] == -4
+    assert res[3] == -64
+
+def test_fortran_frontend_scale():
+    test_string = """
+                    PROGRAM intrinsic_math_test_scale
+                    implicit none
+                    real, dimension(4) :: d
+                    integer, dimension(4) :: d2
+                    real, dimension(5) :: res
+                    CALL intrinsic_math_test_function(d, d2, res)
+                    end
+
+                    SUBROUTINE intrinsic_math_test_function(d, d2, res)
+                    real, dimension(4) :: d
+                    integer, dimension(4) :: d2
+                    real, dimension(5) :: res
+
+                    res(1) = SCALE(d(1), d2(1))
+                    res(2) = SCALE(d(2), d2(2))
+                    res(3) = SCALE(d(3), d2(3))
+                    ! Verifies that we properly replace call even inside a complex expression
+                    res(4) = (SCALE(d(4), d2(4))) + (SCALE(d(4), d2(4))*2)
+                    res(5) = (SCALE(SCALE(d(4), d2(4)), d2(4)))
+
+                    END SUBROUTINE intrinsic_math_test_function
+                    """
+
+    sdfg = fortran_parser.create_sdfg_from_string(test_string, "intrinsic_math_test_modulo", False)
+    sdfg.simplify(verbose=True)
+    sdfg.compile()
+
+    size = 4
+    d = np.full([size], 42, order="F", dtype=np.float32)
+    d[0] = 178.1387e-4
+    d[1] = 5.5
+    d[2] = 5.5
+    d[3] = 42.5
+    d2 = np.full([size], 42, order="F", dtype=np.int32)
+    d2[0] = 5
+    d2[1] = 5
+    d2[2] = 7
+    d2[3] = 9
+    res = np.full([5], 42, order="F", dtype=np.float32)
+    sdfg(d=d, d2=d2, res=res)
+
+    assert abs(res[0] - 0.570043862) < 10**-7
+    assert res[1] == 176.
+    assert res[2] == 704.
+    assert res[3] == 65280.
+    assert res[4] == 11141120.
+
+def test_fortran_frontend_exponent():
+    test_string = """
+                    PROGRAM intrinsic_math_test_exponent
+                    implicit none
+                    real, dimension(4) :: d
+                    integer, dimension(4) :: res
+                    CALL intrinsic_math_test_function(d, res)
+                    end
+
+                    SUBROUTINE intrinsic_math_test_function(d, res)
+                    real, dimension(4) :: d
+                    integer, dimension(4) :: res
+
+                    res(1) = EXPONENT(d(1))
+                    res(2) = EXPONENT(d(2))
+                    res(3) = EXPONENT(d(3))
+                    res(4) = EXPONENT(d(4))
+
+                    END SUBROUTINE intrinsic_math_test_function
+                    """
+
+    sdfg = fortran_parser.create_sdfg_from_string(test_string, "intrinsic_math_test_modulo", False)
+    sdfg.simplify(verbose=True)
+    sdfg.compile()
+
+    size = 4
+    d = np.full([size], 42, order="F", dtype=np.float32)
+    d[0] = 0.0
+    d[1] = 1.0
+    d[2] = 13.0
+    d[3] = 390.0
+    res = np.full([5], 42, order="F", dtype=np.int32)
+    sdfg(d=d, res=res)
+
+    assert res[0] == 0
+    assert res[1] == 1
+    assert res[2] == 4
+    assert res[3] == 9
+
+def test_fortran_frontend_int():
+    test_string = """
+                    PROGRAM intrinsic_math_test_int
+                    implicit none
+                    real, dimension(4) :: d
+                    real, dimension(8) :: d2
+                    integer, dimension(4) :: res
+                    real, dimension(4) :: res2
+                    integer, dimension(8) :: res3
+                    real, dimension(8) :: res4
+                    CALL intrinsic_math_test_function(d, d2, res, res2, res3, res4)
+                    end
+
+                    SUBROUTINE intrinsic_math_test_function(d, d2, res, res2, res3, res4)
+                    integer :: n
+                    real, dimension(4) :: d
+                    real, dimension(8) :: d2
+                    integer, dimension(4) :: res
+                    real, dimension(4) :: res2
+                    integer, dimension(8) :: res3
+                    real, dimension(8) :: res4
+
+                    res(1) = INT(d(1))
+                    res(2) = INT(d(2))
+                    res(3) = INT(d(3))
+                    res(4) = INT(d(4))
+
+                    res2(1) = AINT(d(1))
+                    res2(2) = AINT(d(2))
+                    res2(3) = AINT(d(3))
+                    ! KIND parameter is ignored
+                    res2(4) = AINT(d(4), 4)
+
+                    DO n=1,8
+                        ! KIND parameter is ignored
+                        res3(n) = NINT(d2(n), 4)
+                    END DO
+
+                    DO n=1,8
+                        ! KIND parameter is ignored
+                        res4(n) = ANINT(d2(n), 4)
+                    END DO
+
+                    END SUBROUTINE intrinsic_math_test_function
+                    """
+
+    sdfg = fortran_parser.create_sdfg_from_string(test_string, "intrinsic_math_test_modulo", False)
+    sdfg.simplify(verbose=True)
+    sdfg.compile()
+
+    size = 4
+    d = np.full([size], 42, order="F", dtype=np.float32)
+    d[0] = 1.0
+    d[1] = 1.5
+    d[2] = 42.5
+    d[3] = -42.5
+    d2 = np.full([size*2], 42, order="F", dtype=np.float32)
+    d2[0] = 3.49
+    d2[1] = 3.5
+    d2[2] = 3.51
+    d2[3] = 4
+    d2[4] = -3.49
+    d2[5] = -3.5
+    d2[6] = -3.51
+    d2[7] = -4
+    res = np.full([4], 42, order="F", dtype=np.int32)
+    res2 = np.full([4], 42, order="F", dtype=np.float32)
+    res3 = np.full([8], 42, order="F", dtype=np.int32)
+    res4 = np.full([8], 42, order="F", dtype=np.float32)
+    sdfg(d=d, d2=d2, res=res, res2=res2, res3=res3, res4=res4)
+
+    assert np.array_equal(res, [1, 1, 42, -42])
+
+    assert np.array_equal(res2, [1., 1., 42., -42.])
+
+    assert np.array_equal(res3, [3, 4, 4, 4, -3, -4, -4, -4])
+
+    assert np.array_equal(res4, [3., 4., 4., 4., -3., -4., -4., -4.])
+
+def test_fortran_frontend_real():
+    test_string = """
+                    PROGRAM intrinsic_math_test_real
+                    implicit none
+                    double precision, dimension(2) :: d
+                    real, dimension(2) :: d2
+                    integer, dimension(2) :: d3
+                    double precision, dimension(6) :: res
+                    real, dimension(6) :: res2
+                    CALL intrinsic_math_test_function(d, d2, d3, res, res2)
+                    end
+
+                    SUBROUTINE intrinsic_math_test_function(d, d2, d3, res, res2)
+                    integer :: n
+                    double precision, dimension(2) :: d
+                    real, dimension(2) :: d2
+                    integer, dimension(2) :: d3
+                    double precision, dimension(6) :: res
+                    real, dimension(6) :: res2
+
+                    res(1) = DBLE(d(1))
+                    res(2) = DBLE(d(2))
+                    res(3) = DBLE(d2(1))
+                    res(4) = DBLE(d2(2))
+                    res(5) = DBLE(d3(1))
+                    res(6) = DBLE(d3(2))
+
+                    res2(1) = REAL(d(1))
+                    res2(2) = REAL(d(2))
+                    res2(3) = REAL(d2(1))
+                    res2(4) = REAL(d2(2))
+                    res2(5) = REAL(d3(1))
+                    res2(6) = REAL(d3(2))
+
+                    END SUBROUTINE intrinsic_math_test_function
+                    """
+
+    sdfg = fortran_parser.create_sdfg_from_string(test_string, "intrinsic_math_test_modulo", False)
+    sdfg.simplify(verbose=True)
+    sdfg.compile()
+
+    size = 2
+    d = np.full([size], 42, order="F", dtype=np.float64)
+    d[0] = 7.0
+    d[1] = 13.11
+    d2 = np.full([size], 42, order="F", dtype=np.float32)
+    d2[0] = 7.0
+    d2[1] = 13.11
+    d3 = np.full([size], 42, order="F", dtype=np.int32)
+    d3[0] = 7
+    d3[1] = 13
+
+    res = np.full([size*3], 42, order="F", dtype=np.float64)
+    res2 = np.full([size*3], 42, order="F", dtype=np.float32)
+    sdfg(d=d, d2=d2, d3=d3, res=res, res2=res2)
+
+    assert np.allclose(res, [7.0, 13.11, 7.0, 13.11, 7., 13.])
+    assert np.allclose(res2, [7.0, 13.11, 7.0, 13.11, 7., 13.])
+
+def test_fortran_frontend_trig():
+    test_string = """
+                    PROGRAM intrinsic_math_test_trig
+                    implicit none
+                    real, dimension(3) :: d
+                    real, dimension(6) :: res
+                    CALL intrinsic_math_test_function(d, res)
+                    end
+
+                    SUBROUTINE intrinsic_math_test_function(d, res)
+                    integer :: n
+                    real, dimension(3) :: d
+                    real, dimension(6) :: res
+
+                    DO n=1,3
+                        res(n) = SIN(d(n))
+                    END DO
+
+                    DO n=1,3
+                        res(n+3) = COS(d(n))
+                    END DO
+
+                    END SUBROUTINE intrinsic_math_test_function
+                    """
+
+    sdfg = fortran_parser.create_sdfg_from_string(test_string, "intrinsic_math_test_modulo", False)
+    sdfg.simplify(verbose=True)
+    sdfg.compile()
+
+    size = 3
+    d = np.full([size], 42, order="F", dtype=np.float32)
+    d[0] = 0
+    d[1] = 3.14/2
+    d[2] = 3.14
+
+    res = np.full([size*2], 42, order="F", dtype=np.float32)
+    sdfg(d=d, res=res)
+
+    assert np.allclose(res, [0.0, 0.999999702, 1.59254798E-03, 1.0, 7.96274282E-04, -0.999998748])
+
+def test_fortran_frontend_hyperbolic():
+    test_string = """
+                    PROGRAM intrinsic_math_test_hyperbolic
+                    implicit none
+                    real, dimension(3) :: d
+                    real, dimension(9) :: res
+                    CALL intrinsic_math_test_function(d, res)
+                    end
+
+                    SUBROUTINE intrinsic_math_test_function(d, res)
+                    integer :: n
+                    real, dimension(3) :: d
+                    real, dimension(9) :: res
+
+                    DO n=1,3
+                        res(n) = SINH(d(n))
+                    END DO
+
+                    DO n=1,3
+                        res(n+3) = COSH(d(n))
+                    END DO
+
+                    DO n=1,3
+                        res(n+6) = TANH(d(n))
+                    END DO
+
+                    END SUBROUTINE intrinsic_math_test_function
+                    """
+
+    sdfg = fortran_parser.create_sdfg_from_string(test_string, "intrinsic_math_test_modulo", False)
+    sdfg.simplify(verbose=True)
+    sdfg.compile()
+
+    size = 3
+    d = np.full([size], 42, order="F", dtype=np.float32)
+    d[0] = 0
+    d[1] = 1
+    d[2] = 3.14
+
+    res = np.full([size*3], 42, order="F", dtype=np.float32)
+    sdfg(d=d, res=res)
+
+    assert np.allclose(res, [0.00000000, 1.17520118, 11.5302935, 1.00000000, 1.54308057, 11.5735760, 0.00000000, 0.761594176, 0.996260226])
+
+def test_fortran_frontend_trig_inverse():
+    test_string = """
+                    PROGRAM intrinsic_math_test_hyperbolic
+                    implicit none
+                    real, dimension(3) :: sincos_args
+                    real, dimension(3) :: tan_args
+                    real, dimension(6) :: tan2_args
+                    real, dimension(12) :: res
+                    CALL intrinsic_math_test_function(sincos_args, tan_args, tan2_args, res)
+                    end
+
+                    SUBROUTINE intrinsic_math_test_function(sincos_args, tan_args, tan2_args, res)
+                    integer :: n
+                    real, dimension(3) :: sincos_args
+                    real, dimension(3) :: tan_args
+                    real, dimension(6) :: tan2_args
+                    real, dimension(12) :: res
+
+                    DO n=1,3
+                        res(n) = ASIN(sincos_args(n))
+                    END DO
+
+                    DO n=1,3
+                        res(n+3) = ACOS(sincos_args(n))
+                    END DO
+
+                    DO n=1,3
+                        res(n+6) = ATAN(tan_args(n))
+                    END DO
+
+                    DO n=1,3
+                        res(n+9) = ATAN2(tan2_args(2*n - 1), tan2_args(2*n))
+                    END DO
+
+                    END SUBROUTINE intrinsic_math_test_function
+                    """
+
+    sdfg = fortran_parser.create_sdfg_from_string(test_string, "intrinsic_math_test_modulo", False)
+    sdfg.simplify(verbose=True)
+    sdfg.compile()
+
+    size = 3
+    sincos_args = np.full([size], 42, order="F", dtype=np.float32)
+    sincos_args[0] = -0.5
+    sincos_args[1] = 0.0
+    sincos_args[2] = 1.0
+
+    atan_args = np.full([size], 42, order="F", dtype=np.float32)
+    atan_args[0] = 0.0
+    atan_args[1] = 1.0
+    atan_args[2] = 3.14
+
+    atan2_args = np.full([size*2], 42, order="F", dtype=np.float32)
+    atan2_args[0] = 0.0
+    atan2_args[1] = 1.0
+    atan2_args[2] = 1.0
+    atan2_args[3] = 1.0
+    atan2_args[4] = 1.0
+    atan2_args[5] = 0.0
+
+    res = np.full([size*4], 42, order="F", dtype=np.float32)
+    sdfg(sincos_args=sincos_args, tan_args=atan_args, tan2_args=atan2_args, res=res)
+
+    assert np.allclose(res, [-0.523598790, 0.00000000, 1.57079637, 2.09439516, 1.57079637, 0.00000000, 0.00000000, 0.785398185, 1.26248074, 0.00000000, 0.785398185, 1.57079637])
+
+if __name__ == "__main__":
+
+    test_fortran_frontend_min_max()
+    test_fortran_frontend_sqrt()
+    test_fortran_frontend_abs()
+    test_fortran_frontend_exp()
+    test_fortran_frontend_log()
+    test_fortran_frontend_mod_float()
+    test_fortran_frontend_mod_integer()
+    test_fortran_frontend_modulo_float()
+    test_fortran_frontend_modulo_integer()
+    test_fortran_frontend_floor()
+    test_fortran_frontend_scale()
+    test_fortran_frontend_exponent()
+    test_fortran_frontend_int()
+    test_fortran_frontend_real()
+    test_fortran_frontend_trig()
+    test_fortran_frontend_hyperbolic()
+    test_fortran_frontend_trig_inverse()

From 5669030b513ea719d3d64ffc7ca5a2136a863e79 Mon Sep 17 00:00:00 2001
From: Pratyai Mazumder <pratyai.mazumder@gmail.com>
Date: Wed, 6 Nov 2024 11:02:04 +0100
Subject: [PATCH 18/33] Used valid FORTRAN test program for a couple frontend
 tests + Made `floatlit2string()` convert the FORTRAN real literal strings
 into python floats. (#1733)

Replace some of the invalid fortran test programs with valid ones (that
passes under `gfortran -Wall`). This breaks some of the tests, so add
fix for them too. `test_fortran_frontend_loop1()` still has an invalid
test program, but the nearest valid one breaks for a different reason,
and will be fixed later.
---
 dace/frontend/fortran/ast_components.py |  3 -
 dace/frontend/fortran/ast_utils.py      | 27 ++++++-
 tests/fortran/ast_utils_test.py         | 28 ++++++++
 tests/fortran/fortran_language_test.py  | 96 +++++++++++--------------
 4 files changed, 95 insertions(+), 59 deletions(-)
 create mode 100644 tests/fortran/ast_utils_test.py

diff --git a/dace/frontend/fortran/ast_components.py b/dace/frontend/fortran/ast_components.py
index 332c3a563f..ab0aa9c777 100644
--- a/dace/frontend/fortran/ast_components.py
+++ b/dace/frontend/fortran/ast_components.py
@@ -987,9 +987,6 @@ def block_nonlabel_do_construct(self, node: FASTNode):
                                                   body=ast_internal_classes.Execution_Part_Node(execution=body),
                                                   line_number=do.line_number)
 
-    def real_literal_constant(self, node: FASTNode):
-        return node
-
     def subscript_triplet(self, node: FASTNode):
         if node.string == ":":
             return ast_internal_classes.ParDecl_Node(type="ALL")
diff --git a/dace/frontend/fortran/ast_utils.py b/dace/frontend/fortran/ast_utils.py
index 41cbeff1f9..b52bd31df7 100644
--- a/dace/frontend/fortran/ast_utils.py
+++ b/dace/frontend/fortran/ast_utils.py
@@ -188,8 +188,31 @@ def intlit2string(self, node: ast_internal_classes.Int_Literal_Node):
         return "".join(map(str, node.value))
 
     def floatlit2string(self, node: ast_internal_classes.Real_Literal_Node):
-
-        return "".join(map(str, node.value))
+        # Typecheck and crash early if unexpected.
+        assert hasattr(node, 'value')
+        lit = node.value
+        assert isinstance(lit, str)
+
+        # Fortran "real literals" may have an additional suffix at the end.
+        # Examples:
+        # valid: 1.0 => 1
+        # valid: 1. => 1
+        # valid: 1.e5 => 1e5
+        # valid: 1.d5 => 1e5
+        # valid: 1._kinder => 1 (precondition: somewhere earlier, `integer, parameter :: kinder=8`)
+        # valid: 1.e5_kinder => 1e5
+        # not valid: 1.d5_kinder => 1e5
+        # TODO: Is there a complete spec of the structure of real literals?
+        if '_' in lit:
+            # First, deal with kind specification and remove it altogether, since we know the type anyway.
+            parts = lit.split('_')
+            assert 1 <= len(parts) <= 2, f"{lit} is not a valid fortran literal."
+            lit = parts[0]
+            assert 'd' not in lit, f"{lit} is not a valid fortran literal."
+        if 'd' in lit:
+            # Again, since we know the type anyway, here we just make the s/d/e/ replacement.
+            lit = lit.replace('d', 'e')
+        return f"{float(lit)}"
 
     def boollit2string(self, node: ast_internal_classes.Bool_Literal_Node):
 
diff --git a/tests/fortran/ast_utils_test.py b/tests/fortran/ast_utils_test.py
new file mode 100644
index 0000000000..4ab7b87f35
--- /dev/null
+++ b/tests/fortran/ast_utils_test.py
@@ -0,0 +1,28 @@
+import pytest
+
+from dace.frontend.fortran.ast_internal_classes import Real_Literal_Node
+
+from dace.frontend.fortran.ast_utils import TaskletWriter
+
+
+def test_floatlit2string():
+    def parse(fl: str) -> float:
+        t = TaskletWriter([], [])  # The parameters won't matter.
+        return t.floatlit2string(Real_Literal_Node(value=fl))
+
+    assert parse('1.0') == '1.0'
+    assert parse('1.') == '1.0'
+    assert parse('1.e5') == '100000.0'
+    assert parse('1.d5') == '100000.0'
+    assert parse('1._kinder') == '1.0'
+    assert parse('1.e5_kinder') == '100000.0'
+    with pytest.raises(AssertionError):
+        parse('1.d5_kinder')
+    with pytest.raises(AssertionError):
+        parse('1._kinder_kinder')
+    with pytest.raises(ValueError, match="could not convert string to float"):
+        parse('1.2.0')
+    with pytest.raises(ValueError, match="could not convert string to float"):
+        parse('1.d0d0')
+    with pytest.raises(ValueError, match="could not convert string to float"):
+        parse('foo')
diff --git a/tests/fortran/fortran_language_test.py b/tests/fortran/fortran_language_test.py
index 32ab23714b..9034ba20f3 100644
--- a/tests/fortran/fortran_language_test.py
+++ b/tests/fortran/fortran_language_test.py
@@ -1,22 +1,8 @@
 # Copyright 2023 ETH Zurich and the DaCe authors. All rights reserved.
 
-from fparser.common.readfortran import FortranStringReader
-from fparser.common.readfortran import FortranFileReader
-from fparser.two.parser import ParserFactory
-import sys, os
 import numpy as np
-import pytest
 
-
-from dace import SDFG, SDFGState, nodes, dtypes, data, subsets, symbolic
 from dace.frontend.fortran import fortran_parser
-from fparser.two.symbol_table import SymbolTable
-from dace.sdfg import utils as sdutil
-
-import dace.frontend.fortran.ast_components as ast_components
-import dace.frontend.fortran.ast_transforms as ast_transforms
-import dace.frontend.fortran.ast_utils as ast_utils
-import dace.frontend.fortran.ast_internal_classes as ast_internal_classes
 
 
 def test_fortran_frontend_real_kind_selector():
@@ -24,23 +10,25 @@ def test_fortran_frontend_real_kind_selector():
     Tests that the size intrinsics are correctly parsed and translated to DaCe.
     """
     test_string = """
-                    PROGRAM real_kind_selector_test
-                    implicit none
-                    INTEGER, PARAMETER :: JPRB = SELECTED_REAL_KIND(13,300)
-                    INTEGER, PARAMETER :: JPIM = SELECTED_INT_KIND(9)
-                    REAL(KIND=JPRB) d(4)
-                    CALL real_kind_selector_test_function(d)
-                    end
-
-                    SUBROUTINE real_kind_selector_test_function(d)
-                    REAL(KIND=JPRB) d(4)
-                    INTEGER(KIND=JPIM) i
-
-                    i=7
-                    d(2)=5.5+i
-                    
-                    END SUBROUTINE real_kind_selector_test_function
-                    """
+program real_kind_selector_test
+  implicit none
+  integer, parameter :: JPRB = selected_real_kind(13, 300)
+  real(KIND=JPRB) d(4)
+  call real_kind_selector_test_function(d)
+end
+
+subroutine real_kind_selector_test_function(d)
+  implicit none
+  integer, parameter :: JPRB = selected_real_kind(13, 300)
+  integer, parameter :: JPIM = selected_int_kind(9)
+  real(KIND=JPRB) d(4)
+  integer(KIND=JPIM) i
+
+  i = 7
+  d(2) = 5.5 + i
+
+end subroutine real_kind_selector_test_function
+"""
     sdfg = fortran_parser.create_sdfg_from_string(test_string, "real_kind_selector_test")
     sdfg.simplify(verbose=True)
     a = np.full([4], 42, order="F", dtype=np.float64)
@@ -129,30 +117,30 @@ def test_fortran_frontend_function_statement1():
     """
     Tests that the function statement are correctly removed recursively.
     """
-    
-    test_string = """
-                    PROGRAM function_statement1_test
-                    implicit none
-                    double precision d(3,4,5)
-                    CALL function_statement1_test_function(d)
-                    end
 
-                    SUBROUTINE function_statement1_test_function(d)
-                   double precision d(3,4,5)
-                   double precision :: PTARE,RTT(2),FOEDELTA,FOELDCP
-                   double precision :: RALVDCP(2),RALSDCP(2),RES
-
-                    FOEDELTA (PTARE) = MAX (0.0,SIGN(1.0,PTARE-RTT(1)))
-                    FOELDCP ( PTARE ) = FOEDELTA(PTARE)*RALVDCP(1) + (1.0-FOEDELTA(PTARE))*RALSDCP(1)
-
-                    RTT(1)=4.5
-                    RALVDCP(1)=4.9
-                    RALSDCP(1)=5.1
-                    d(1,1,1)=FOELDCP(3.0)
-                    RES=FOELDCP(3.0)
-                   d(1,1,2)=RES                 
-                   END SUBROUTINE function_statement1_test_function
-                    """
+    test_string = """
+program function_statement1_test
+  implicit none
+  double precision d(3, 4, 5)
+  call function_statement1_test_function(d)
+end
+
+subroutine function_statement1_test_function(d)
+  double precision d(3, 4, 5)
+  double precision :: PTARE, RTT(2), FOEDELTA, FOELDCP
+  double precision :: RALVDCP(2), RALSDCP(2), RES
+
+  FOEDELTA(PTARE) = max(0.0, sign(1.d0, PTARE - RTT(1)))
+  FOELDCP(PTARE) = FOEDELTA(PTARE)*RALVDCP(1) + (1.0 - FOEDELTA(PTARE))*RALSDCP(1)
+
+  RTT(1) = 4.5
+  RALVDCP(1) = 4.9
+  RALSDCP(1) = 5.1
+  d(1, 1, 1) = FOELDCP(3.d0)
+  RES = FOELDCP(3.d0)
+  d(1, 1, 2) = RES
+end subroutine function_statement1_test_function
+"""
     sdfg = fortran_parser.create_sdfg_from_string(test_string, "function_statement1_test")
     sdfg.simplify(verbose=True)
     d = np.full([3, 4, 5], 42, order="F", dtype=np.float64)

From fad217586184790ef2d880b1fd525f09fb4aed44 Mon Sep 17 00:00:00 2001
From: Roman Cattaneo <romanc@users.noreply.github.com>
Date: Wed, 6 Nov 2024 12:48:39 +0100
Subject: [PATCH 19/33] CI[pyFV3]: retry even when connection is refused
 (#1734)

According to @phschaad, the pyFV3 workflow occasionally fails with
connection refused errors when attempting to download the test data set
for regression testing. This PR configures `wget` to retry even in case
of fatal connection errors (like 404 (not found) or 503 (connection
refused)).

Let's see if this helps in the short term. In the long run, we should
think about leveraging caches for that data because it rarely changes
and it's kind of a wast to download it every time from scratch.

Follow-up PR from
https://github.com/spcl/dace/pull/1731#issuecomment-2458989370.

/cc @FlorianDeconinck FYI

Co-authored-by: Roman Cattaneo <>
---
 .github/workflows/pyFV3-ci.yml | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/.github/workflows/pyFV3-ci.yml b/.github/workflows/pyFV3-ci.yml
index 85c864e475..852b887cdb 100644
--- a/.github/workflows/pyFV3-ci.yml
+++ b/.github/workflows/pyFV3-ci.yml
@@ -53,11 +53,11 @@ jobs:
           cd pyFV3
           mkdir -p test_data
           cd test_data
-          wget https://portal.nccs.nasa.gov/datashare/astg/smt/pace-regression-data/8.1.3_c12_6ranks_standard.D_SW.tar.gz
+          wget --retry-connrefused https://portal.nccs.nasa.gov/datashare/astg/smt/pace-regression-data/8.1.3_c12_6ranks_standard.D_SW.tar.gz
           tar -xzvf 8.1.3_c12_6ranks_standard.D_SW.tar.gz
-          wget https://portal.nccs.nasa.gov/datashare/astg/smt/pace-regression-data/8.1.3_c12_6ranks_standard.RiemSolver3.tar.gz
+          wget --retry-connrefused https://portal.nccs.nasa.gov/datashare/astg/smt/pace-regression-data/8.1.3_c12_6ranks_standard.RiemSolver3.tar.gz
           tar -xzvf 8.1.3_c12_6ranks_standard.RiemSolver3.tar.gz
-          wget https://portal.nccs.nasa.gov/datashare/astg/smt/pace-regression-data/8.1.3_c12_6ranks_standard.Remapping.tar.gz
+          wget --retry-connrefused https://portal.nccs.nasa.gov/datashare/astg/smt/pace-regression-data/8.1.3_c12_6ranks_standard.Remapping.tar.gz
           tar -xzvf 8.1.3_c12_6ranks_standard.Remapping.tar.gz
           cd ../..
       # Clean up caches between run for stale un-expanded SDFG to trip the build system (NDSL side issue)

From d295a6290f09b5455797ccf53dd3e47924864083 Mon Sep 17 00:00:00 2001
From: Pratyai Mazumder <pratyai.mazumder@gmail.com>
Date: Thu, 7 Nov 2024 08:03:37 +0100
Subject: [PATCH 20/33] Fix pure reduce expansion for squeezed output memlets.
 (#1709)

It was producing wrong indices for the initialization kernel, which
would not work for some simple valid SDFGs (see the demo in the test).
---
 dace/libraries/standard/nodes/reduce.py |  2 +-
 tests/library/reduce_test.py            | 74 ++++++++++++++++++++-----
 2 files changed, 62 insertions(+), 14 deletions(-)

diff --git a/dace/libraries/standard/nodes/reduce.py b/dace/libraries/standard/nodes/reduce.py
index fa231c07f2..970dfcef3a 100644
--- a/dace/libraries/standard/nodes/reduce.py
+++ b/dace/libraries/standard/nodes/reduce.py
@@ -103,7 +103,7 @@ def expansion(node: 'Reduce', state: SDFGState, sdfg: SDFG):
                 'reduce_init', {'_o%d' % i: '0:%s' % symstr(d)
                                 for i, d in enumerate(outedge.data.subset.size())}, {},
                 '__out = %s' % node.identity,
-                {'__out': dace.Memlet.simple('_out', ','.join(['_o%d' % i for i in range(output_dims)]))},
+                {'__out': dace.Memlet.simple('_out', ','.join(['_o%d' % i for i in osqdim]))},
                 external_edges=True)
         else:
             nstate = nsdfg.add_state()
diff --git a/tests/library/reduce_test.py b/tests/library/reduce_test.py
index 8e4b2153f0..bb448226db 100644
--- a/tests/library/reduce_test.py
+++ b/tests/library/reduce_test.py
@@ -1,35 +1,82 @@
 # Copyright 2019-2021 ETH Zurich and the DaCe authors. All rights reserved.
-import dace
 import numpy as np
 import pytest
+
+import dace
 import dace.libraries.standard as std
+from dace import SDFG, Memlet
+
+C_in, C_out, H, K, N, W = (dace.symbol(s, dace.int64) for s in ('C_in', 'C_out', 'H', 'K', 'N', 'W'))
+
+
+def make_sdfg():
+    g = SDFG('prog')
+    g.add_array('A', (N, 1, 1, C_in, C_out), dace.float32,
+                strides=(C_in * C_out, C_in * C_out, C_in * C_out, C_out, 1))
+    g.add_array('C', (N, H, W, C_out), dace.float32,
+                strides=(C_out * H * W, C_out * W, C_out, 1))
+
+    st0 = g.add_state('st0', is_start_block=True)
+    st = st0
+
+    A = st.add_access('A')
+    C = st.add_access('C')
+    R = st.add_reduce('lambda x, y: x + y', [1, 2, 3], 0)
+    st.add_nedge(A, R, Memlet(expr='A[0:N, 0, 0, 0:C_in, 0:C_out]'))
+    st.add_nedge(R, C, Memlet(expr='C[0:N, 5, 5, 0:C_out]'))
+
+    return g, R
+
+
+def test_library_node_expand_reduce_pure():
+    n, cin, cout = 7, 7, 7
+    h, k, w = 25, 35, 45
+    A = np.ones((n, 1, 1, cin, cout), np.float32)
+
+    g, R = make_sdfg()
+    R.implementation = 'pure-seq'
+    g.validate()
+    g.compile()
+
+    wantC = np.ones((n, h, w, cout), np.float32) * 42
+    g(A=A, C=wantC, N=n, C_in=cin, C_out=cout, H=h, K=k, W=w)
+
+    g, R = make_sdfg()
+    R.implementation = 'pure'
+    g.validate()
+    g.compile()
+
+    gotC = np.ones((n, h, w, cout), np.float32) * 42
+    g(A=A, C=gotC, N=n, C_in=cin, C_out=cout, H=h, K=k, W=w)
+    assert np.allclose(wantC, gotC)
+
 
 _params = ['pure', 'CUDA (device)', 'pure-seq', 'GPUAuto']
-  
 
 
 @pytest.mark.gpu
 @pytest.mark.parametrize('impl', _params)
 def test_multidim_gpu(impl):
-
     test_cases = [([1, 64, 60, 60], (0, 2, 3), [64], np.float32),
-                    ([8, 512, 4096], (0,1), [4096], np.float32),
-                    ([8, 512, 4096], (0,1), [4096], np.float64),
-                    ([1024, 8], (0), [8], np.float32),
-                    ([111, 111, 111], (0,1), [111], np.float64),
-                    ([111, 111, 111], (1,2), [111], np.float64),
-                    ([1000000], (0), [1], np.float64),
-                    ([1111111], (0), [1], np.float64),
-                    ([123,21,26,8], (1,2), [123,8], np.float32),
-                    ([2, 512, 2], (0,2), [512], np.float32),
-                    ([512, 555, 257], (0,2), [555], np.float64)]
+                  ([8, 512, 4096], (0, 1), [4096], np.float32),
+                  ([8, 512, 4096], (0, 1), [4096], np.float64),
+                  ([1024, 8], (0), [8], np.float32),
+                  ([111, 111, 111], (0, 1), [111], np.float64),
+                  ([111, 111, 111], (1, 2), [111], np.float64),
+                  ([1000000], (0), [1], np.float64),
+                  ([1111111], (0), [1], np.float64),
+                  ([123, 21, 26, 8], (1, 2), [123, 8], np.float32),
+                  ([2, 512, 2], (0, 2), [512], np.float32),
+                  ([512, 555, 257], (0, 2), [555], np.float64)]
 
     for in_shape, ax, out_shape, dtype in test_cases:
         print(in_shape, ax, out_shape, dtype)
         axes = ax
+
         @dace.program
         def multidimred(a, b):
             b[:] = np.sum(a, axis=axes)
+
         a = np.random.rand(*in_shape).astype(dtype)
         b = np.random.rand(*out_shape).astype(dtype)
         sdfg = multidimred.to_sdfg(a, b)
@@ -45,3 +92,4 @@ def multidimred(a, b):
 if __name__ == '__main__':
     for p in _params:
         test_multidim_gpu(p)
+    test_library_node_expand_reduce_pure()

From fb7f56c0b6f66c9de2247d38235da7f813bccf41 Mon Sep 17 00:00:00 2001
From: Pratyai Mazumder <pratyai.mazumder@gmail.com>
Date: Fri, 8 Nov 2024 04:29:05 +0100
Subject: [PATCH 21/33] Make the import of `typing.Literal` portable between
 python versions 3.7 and 3.12 (#1700)

Addresses this problem: https://stackoverflow.com/a/67193166

This would be useful if we want to use this library to compare graphs in
the unit tests.
---
 dace/cli/sdfg_diff.py | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/dace/cli/sdfg_diff.py b/dace/cli/sdfg_diff.py
index 2ec0a3adf4..ed661b8c25 100644
--- a/dace/cli/sdfg_diff.py
+++ b/dace/cli/sdfg_diff.py
@@ -7,7 +7,11 @@
 import os
 import platform
 import tempfile
-from typing import Dict, Literal, Set, Tuple, Union
+from typing import Dict, Set, Tuple, Union
+try:
+    from typing import Literal
+except ImportError:
+    from typing_extensions import Literal
 
 import dace
 from dace import memlet as mlt

From 2911a4516ee6722adcdb02842ef5e0ccd2b6f8b6 Mon Sep 17 00:00:00 2001
From: Pratyai Mazumder <pratyai.mazumder@gmail.com>
Date: Fri, 8 Nov 2024 08:26:23 +0100
Subject: [PATCH 22/33] Fix `cpp.reshape_strides()`, which currently cannot
 handle inputs that tries to increase the number of dimensions after the
 reshape. (#1692)

Fix the issue with cpp codegen, where it currently cannot handle inputs:
```c++
cpp.reshape_strides(Range([(0, 4, 1), (0, 5, 1)]), None, None, [2, 3, 5])
```
and crashes with an index error.

Also fixes #1690 where `RedundantArray` was producing a (valid) graph
that triggered this.
---
 dace/codegen/targets/cpp.py |   3 +-
 tests/codegen/cpp_test.py   | 221 ++++++++++++++++++++++++++++++++++++
 2 files changed, 223 insertions(+), 1 deletion(-)
 create mode 100644 tests/codegen/cpp_test.py

diff --git a/dace/codegen/targets/cpp.py b/dace/codegen/targets/cpp.py
index ed52bd093a..3f02d0e6cc 100644
--- a/dace/codegen/targets/cpp.py
+++ b/dace/codegen/targets/cpp.py
@@ -417,9 +417,10 @@ def reshape_strides(subset, strides, original_strides, copy_shape):
     dims = len(copy_shape)
 
     reduced_tile_sizes = [ts for ts, s in zip(subset.tile_sizes, original_copy_shape) if s != 1]
+    reduced_tile_sizes += [1] * (dims - len(reduced_tile_sizes))  # Pad the remainder with 1s to maintain dimensions.
 
     reshaped_copy = copy_shape + [ts for ts in subset.tile_sizes if ts != 1]
-    reshaped_copy[:len(copy_shape)] = [s / ts for s, ts in zip(copy_shape, reduced_tile_sizes)]
+    reshaped_copy[:len(copy_shape)] = [s // ts for s, ts in zip(copy_shape, reduced_tile_sizes)]
 
     new_strides = [0] * len(reshaped_copy)
     elements_remaining = functools.reduce(sp.Mul, copy_shape, 1)
diff --git a/tests/codegen/cpp_test.py b/tests/codegen/cpp_test.py
new file mode 100644
index 0000000000..667997216b
--- /dev/null
+++ b/tests/codegen/cpp_test.py
@@ -0,0 +1,221 @@
+# Copyright 2019-2024 ETH Zurich and the DaCe authors. All rights reserved.
+
+from functools import reduce
+from operator import mul
+from typing import Dict, Collection
+
+import dace
+from dace import SDFG, Memlet
+from dace.codegen.targets import cpp
+from dace.sdfg.state import SDFGState
+from dace.subsets import Range
+from dace.transformation.dataflow import RedundantArray
+
+
+def _add_map_with_connectors(st: SDFGState, name: str, ndrange: Dict[str, str],
+                             en_conn_bases: Collection[str] = None, ex_conn_bases: Collection[str] = None):
+    en, ex = st.add_map(name, ndrange)
+    if en_conn_bases:
+        for c in en_conn_bases:
+            en.add_in_connector(f"IN_{c}")
+            en.add_out_connector(f"OUT_{c}")
+    if ex_conn_bases:
+        for c in ex_conn_bases:
+            ex.add_in_connector(f"IN_{c}")
+            ex.add_out_connector(f"OUT_{c}")
+    return en, ex
+
+
+def test_reshape_strides_multidim_array_all_dims_unit():
+    r = Range([(0, 0, 1), (0, 0, 1)])
+
+    # To smaller-sized shape
+    target_dims = [1]
+    assert reduce(mul, r.size_exact()) == reduce(mul, target_dims)
+    reshaped, strides = cpp.reshape_strides(r, None, None, target_dims)
+    assert reshaped == [1]
+    assert strides == [1]
+
+    # To equal-sized shape
+    target_dims = [1, 1]
+    assert reduce(mul, r.size_exact()) == reduce(mul, target_dims)
+    reshaped, strides = cpp.reshape_strides(r, None, None, target_dims)
+    assert reshaped == [1, 1]
+    assert strides == [1, 1]
+
+    # To larger-sized shape
+    target_dims = [1, 1, 1]
+    assert reduce(mul, r.size_exact()) == reduce(mul, target_dims)
+    reshaped, strides = cpp.reshape_strides(r, None, None, target_dims)
+    assert reshaped == [1, 1, 1]
+    assert strides == [1, 1, 1]
+
+
+def test_reshape_strides_multidim_array_some_dims_unit():
+    r = Range([(0, 1, 1), (0, 0, 1)])
+
+    # To smaller-sized shape
+    target_dims = [2]
+    assert reduce(mul, r.size_exact()) == reduce(mul, target_dims)
+    reshaped, strides = cpp.reshape_strides(r, None, None, target_dims)
+    assert reshaped == target_dims
+    assert strides == [1]
+
+    # To equal-sized shape
+    target_dims = [2, 1]
+    assert reduce(mul, r.size_exact()) == reduce(mul, target_dims)
+    reshaped, strides = cpp.reshape_strides(r, None, None, target_dims)
+    assert reshaped == target_dims
+    assert strides == [1, 1]
+    # To equal-sized shape, but units first.
+    target_dims = [1, 2]
+    assert reduce(mul, r.size_exact()) == reduce(mul, target_dims)
+    reshaped, strides = cpp.reshape_strides(r, None, None, target_dims)
+    assert reshaped == target_dims
+    assert strides == [2, 1]
+
+    # To larger-sized shape.
+    target_dims = [2, 1, 1]
+    assert reduce(mul, r.size_exact()) == reduce(mul, target_dims)
+    reshaped, strides = cpp.reshape_strides(r, None, None, target_dims)
+    assert reshaped == target_dims
+    assert strides == [1, 1, 1]
+    # To larger-sized shape, but units first.
+    target_dims = [1, 1, 2]
+    assert reduce(mul, r.size_exact()) == reduce(mul, target_dims)
+    reshaped, strides = cpp.reshape_strides(r, None, None, target_dims)
+    assert reshaped == target_dims
+    assert strides == [2, 2, 1]
+
+
+def test_reshape_strides_multidim_array_different_shape():
+    r = Range([(0, 4, 1), (0, 5, 1)])
+
+    # To smaller-sized shape
+    target_dims = [30]
+    assert reduce(mul, r.size_exact()) == reduce(mul, target_dims)
+    reshaped, strides = cpp.reshape_strides(r, None, None, target_dims)
+    assert reshaped == target_dims
+    assert strides == [1]
+
+    # To equal-sized shape
+    target_dims = [15, 2]
+    assert reduce(mul, r.size_exact()) == reduce(mul, target_dims)
+    reshaped, strides = cpp.reshape_strides(r, None, None, target_dims)
+    assert reshaped == target_dims
+    assert strides == [2, 1]
+
+    # To larger-sized shape
+    target_dims = [3, 5, 2]
+    assert reduce(mul, r.size_exact()) == reduce(mul, target_dims)
+    reshaped, strides = cpp.reshape_strides(r, None, None, target_dims)
+    assert reshaped == target_dims
+    assert strides == [10, 2, 1]
+
+
+def test_reshape_strides_from_strided_range():
+    r = Range([(0, 4, 2), (0, 6, 2)])
+
+    # To smaller-sized shape
+    target_dims = [12]
+    assert reduce(mul, r.size_exact()) == reduce(mul, target_dims)
+    reshaped, strides = cpp.reshape_strides(r, None, None, target_dims)
+    assert reshaped == target_dims
+    assert strides == [1]
+
+    # To equal-sized shape
+    target_dims = [4, 3]
+    assert reduce(mul, r.size_exact()) == reduce(mul, target_dims)
+    reshaped, strides = cpp.reshape_strides(r, None, None, target_dims)
+    assert reshaped == target_dims
+    assert strides == [3, 1]
+
+    # To larger-sized shape
+    target_dims = [2, 3, 2]
+    assert reduce(mul, r.size_exact()) == reduce(mul, target_dims)
+    reshaped, strides = cpp.reshape_strides(r, None, None, target_dims)
+    assert reshaped == target_dims
+    assert strides == [6, 2, 1]
+
+
+def test_reshape_strides_from_strided_and_offset_range():
+    r = Range([(10, 14, 2), (10, 16, 2)])
+
+    # To smaller-sized shape
+    target_dims = [12]
+    assert reduce(mul, r.size_exact()) == reduce(mul, target_dims)
+    reshaped, strides = cpp.reshape_strides(r, None, None, target_dims)
+    assert reshaped == target_dims
+    assert strides == [1]
+
+    # To equal-sized shape
+    target_dims = [4, 3]
+    assert reduce(mul, r.size_exact()) == reduce(mul, target_dims)
+    reshaped, strides = cpp.reshape_strides(r, None, None, target_dims)
+    assert reshaped == target_dims
+    assert strides == [3, 1]
+
+    # To larger-sized shape
+    target_dims = [2, 3, 2]
+    assert reduce(mul, r.size_exact()) == reduce(mul, target_dims)
+    reshaped, strides = cpp.reshape_strides(r, None, None, target_dims)
+    assert reshaped == target_dims
+    assert strides == [6, 2, 1]
+
+
+def redundant_array_crashes_codegen_test_original_graph():
+    g = SDFG('prog')
+    g.add_array('A', (5, 5), dace.float32)
+    g.add_array('b', (1,), dace.float32, transient=True)
+    g.add_array('c', (5, 5), dace.float32, transient=True)
+
+    st0 = g.add_state('st0', is_start_block=True)
+    st = st0
+
+    # Make a single map that copies A[i, j] to a transient "scalar" b, then copies that out to a transient array
+    # c[i, j], then finally back to A[i, j] again.
+    A = st.add_access('A')
+    en, ex = _add_map_with_connectors(st, 'm0', {'i': '0:1', 'j': '0:1'}, ['A'], ['A'])
+    st.add_edge(A, None, en, 'IN_A', Memlet(expr='A[0:1, 0:1]'))
+    b = st.add_access('b')
+    st.add_edge(en, 'OUT_A', b, None, Memlet(expr='A[i, j] -> b[0]'))
+    c = st.add_access('c')
+    st.add_nedge(b, c, Memlet(expr='b[0] -> c[i, j]'))
+    st.add_edge(c, None, ex, 'IN_A', Memlet(expr='c[i, j] -> A[i, j]'))
+    A = st.add_access('A')
+    st.add_edge(ex, 'OUT_A', A, None, Memlet(expr='A[0:1, 0:1]'))
+    st0.fill_scope_connectors()
+
+    g.validate()
+    g.compile()
+    return g
+
+
+def test_redundant_array_does_not_crash_codegen_but_produces_bad_graph_now():
+    """
+    This test demonstrates the bug in CPP Codegen that the [PR](https://github.com/spcl/dace/pull/1692) fixes.
+    """
+    g = redundant_array_crashes_codegen_test_original_graph()
+    g.apply_transformations(RedundantArray)
+    g.validate()
+    g.compile()
+
+    # NOTE: The produced graph still has bug. So, let's test for its existence.
+    assert len(g.states()) == 1
+    st = g.states()[0]
+    assert len(st.source_nodes()) == 1
+    src = st.source_nodes()[0]
+    assert len(st.out_edges(src)) == 1
+    e = st.out_edges(src)[0]
+    # This is the wrong part. These symbols are not available in this scope.
+    assert e.data.free_symbols == {'i', 'j'}
+
+
+if __name__ == '__main__':
+    test_reshape_strides_multidim_array_all_dims_unit()
+    test_reshape_strides_multidim_array_some_dims_unit()
+    test_reshape_strides_multidim_array_different_shape()
+    test_reshape_strides_from_strided_range()
+    test_reshape_strides_from_strided_and_offset_range()
+
+    test_redundant_array_does_not_crash_codegen_but_produces_bad_graph_now()

From d61122d6122b7fe2c515e30442ae3ab77a47bb11 Mon Sep 17 00:00:00 2001
From: Tal Ben-Nun <tbennun@users.noreply.github.com>
Date: Fri, 8 Nov 2024 00:42:55 -0800
Subject: [PATCH 23/33] Fix type inference and code generation for typeclasses
 and numpy types (#1725)

Fixes #1710
Supersedes #1721
---
 dace/codegen/cppunparse.py                 |  2 +
 dace/codegen/targets/cpp.py                |  4 ++
 dace/codegen/targets/fpga.py               |  6 ++-
 dace/codegen/targets/framecode.py          |  7 +++-
 dace/codegen/targets/intel_fpga.py         | 33 ++++++++--------
 dace/dtypes.py                             | 44 ++++++++++++++++------
 dace/runtime/include/dace/reduction.h      | 18 +++++++--
 dace/runtime/include/dace/types.h          |  1 +
 dace/sdfg/infer_types.py                   |  3 --
 dace/sdfg/validation.py                    |  2 +-
 tests/passes/dead_code_elimination_test.py | 41 +++++++++++++-------
 11 files changed, 112 insertions(+), 49 deletions(-)

diff --git a/dace/codegen/cppunparse.py b/dace/codegen/cppunparse.py
index c375147930..e5e5a57f09 100644
--- a/dace/codegen/cppunparse.py
+++ b/dace/codegen/cppunparse.py
@@ -349,6 +349,8 @@ def _Assign(self, t):
                             # if the veclen is greater than one, this should be defined with a vector data type
                             self.write("{}{} ".format(dace.dtypes._OCL_VECTOR_TYPES[inferred_type.type],
                                                       inferred_type.veclen))
+                        elif self.language == dace.dtypes.Language.OpenCL:
+                            self.write(dace.dtypes._OCL_TYPES[inferred_type.type] + " ")
                         else:
                             self.write(dace.dtypes._CTYPES[inferred_type.type] + " ")
                     else:
diff --git a/dace/codegen/targets/cpp.py b/dace/codegen/targets/cpp.py
index 3f02d0e6cc..911a792ac9 100644
--- a/dace/codegen/targets/cpp.py
+++ b/dace/codegen/targets/cpp.py
@@ -1339,6 +1339,10 @@ def visit_Attribute(self, node):
         attrname = rname(node)
         module_name = attrname[:attrname.rfind(".")]
         func_name = attrname[attrname.rfind(".") + 1:]
+        if module_name == 'dace' and isinstance(getattr(dace, func_name, False), dtypes.typeclass):
+            # A type definition
+            dtype: dtypes.typeclass = getattr(dace, func_name)
+            return ast.copy_location(ast.Name(id=dtype.ctype, ctx=ast.Load), node)
         if module_name in dtypes._ALLOWED_MODULES:
             cppmodname = dtypes._ALLOWED_MODULES[module_name]
             return ast.copy_location(ast.Name(id=(cppmodname + func_name), ctx=ast.Load), node)
diff --git a/dace/codegen/targets/fpga.py b/dace/codegen/targets/fpga.py
index 0c74d6ec07..61ba9f95ad 100644
--- a/dace/codegen/targets/fpga.py
+++ b/dace/codegen/targets/fpga.py
@@ -2112,7 +2112,11 @@ def _generate_MapEntry(self, sdfg: SDFG, cfg: ControlFlowRegion, dfg: StateSubgr
                                 end_type = None
                             if end_type is not None:
                                 if np.dtype(end_type.dtype.type) > np.dtype('uint32'):
-                                    loop_var_type = end_type.ctype
+                                    v = dace.config.Config.get("compiler", "fpga", "vendor")
+                                    if v.casefold() == 'intel_fpga'.casefold():
+                                        loop_var_type = end_type.ocltype
+                                    else:
+                                        loop_var_type = end_type.ctype
                                 elif np.issubdtype(np.dtype(end_type.dtype.type), np.unsignedinteger):
                                     loop_var_type = "size_t"
                     except (UnboundLocalError):
diff --git a/dace/codegen/targets/framecode.py b/dace/codegen/targets/framecode.py
index d71ea40fee..0b8fa739fe 100644
--- a/dace/codegen/targets/framecode.py
+++ b/dace/codegen/targets/framecode.py
@@ -947,7 +947,12 @@ def generate_code(self,
             if not is_top_level and isvarName in sdfg.parent_nsdfg_node.symbol_mapping:
                 continue
             isvar = data.Scalar(isvarType)
-            callsite_stream.write('%s;\n' % (isvar.as_arg(with_types=True, name=isvarName)), sdfg)
+            if (schedule in (dtypes.ScheduleType.FPGA_Device, dtypes.ScheduleType.FPGA_Multi_Pumped)
+                    and config.Config.get('compiler', 'fpga', 'vendor').lower() == 'intel_fpga'):
+                # Emit OpenCL type
+                callsite_stream.write(f'{isvarType.ocltype} {isvarName};\n', sdfg)
+            else:
+                callsite_stream.write('%s;\n' % (isvar.as_arg(with_types=True, name=isvarName)), sdfg)
             self.dispatcher.defined_vars.add(isvarName, disp.DefinedType.Scalar, isvarType.ctype)
 
         callsite_stream.write('\n', sdfg)
diff --git a/dace/codegen/targets/intel_fpga.py b/dace/codegen/targets/intel_fpga.py
index 513dc0bbfc..9437dccbe3 100644
--- a/dace/codegen/targets/intel_fpga.py
+++ b/dace/codegen/targets/intel_fpga.py
@@ -169,15 +169,16 @@ def get_generated_codeobjects(self):
                                    "cpp",
                                    IntelFPGACodeGen,
                                    "Intel FPGA",
-                                   target_type="host")
+                                   target_type="host",
+                                   sdfg=self._global_sdfg)
 
         kernel_code_objs = [
-            CodeObject(kernel_name, code, "cl", IntelFPGACodeGen, "Intel FPGA", target_type="device")
+            CodeObject(kernel_name, code, "cl", IntelFPGACodeGen, "Intel FPGA", target_type="device", sdfg=self._global_sdfg)
             for (kernel_name, code, _) in self._kernel_codes
         ]
         # add the util header if present
         other_code_objs = [
-            CodeObject(file_name, code.getvalue(), "cl", IntelFPGACodeGen, "Intel FPGA", target_type="device")
+            CodeObject(file_name, code.getvalue(), "cl", IntelFPGACodeGen, "Intel FPGA", target_type="device", sdfg=self._global_sdfg)
             for (file_name, code) in self._other_codes.items()
         ]
 
@@ -299,8 +300,8 @@ def make_kernel_argument(self, data, var_name, is_output, with_vectorization):
             return "__global volatile  {}* restrict {}".format(vec_type, var_name)
         elif isinstance(data, dace.data.Stream):
             return None  # Streams are global objects
-        else:
-            return data.as_arg(with_types=True, name=var_name)
+        else: # Scalar or structure
+            return f'{data.dtype.ocltype} {var_name}'
 
     @staticmethod
     def generate_unroll_loop_pre(kernel_stream, factor, sdfg, cfg, state_id, node):
@@ -570,8 +571,9 @@ def generate_module(self, sdfg, cfg, state, kernel_name, module_name, subgraph,
             arg = self.make_kernel_argument(p, pname, is_output, True)
 
             if arg is not None:
-                #change c type long long to opencl type long
-                arg = arg.replace("long long", "long")
+                #change c type to opencl type
+                if arg in dtypes._CTYPES_TO_OCLTYPES:
+                    arg = dtypes._CTYPES_TO_OCLTYPES[arg]
 
                 kernel_args_opencl.append(arg)
                 kernel_args_host.append(p.as_arg(True, name=pname))
@@ -733,7 +735,7 @@ def generate_nsdfg_header(self, sdfg, cfg, state, state_id, node, memlet_referen
         arguments = [f'{atype} {aname}' for atype, aname, _ in memlet_references]
         fsyms = node.sdfg.used_symbols(all_symbols=False, keep_defined_in_mapping=True)
         arguments += [
-            f'{node.sdfg.symbols[aname].as_arg(aname)}' for aname in sorted(node.symbol_mapping.keys())
+            f'{node.sdfg.symbols[aname].ocltype} {aname}' for aname in sorted(node.symbol_mapping.keys())
             if aname in fsyms and aname not in sdfg.constants
         ]
         arguments = ', '.join(arguments)
@@ -769,8 +771,9 @@ def generate_nsdfg_arguments(self, sdfg, cfg, dfg, state, node):
             ptrname = cpp.ptr(in_memlet.data, desc, sdfg, self._frame)
             defined_type, defined_ctype = self._dispatcher.defined_vars.get(ptrname, 1)
 
-            #change c type long long to opencl type long
-            defined_ctype = defined_ctype.replace("long long", "long")
+            #change c type to opencl type
+            if defined_ctype in dtypes._CTYPES_TO_OCLTYPES:
+                defined_ctype = dtypes._CTYPES_TO_OCLTYPES[defined_ctype]
 
             if isinstance(desc, dace.data.Array) and (desc.storage == dtypes.StorageType.FPGA_Global
                                                       or desc.storage == dtypes.StorageType.FPGA_Local):
@@ -822,9 +825,9 @@ def generate_nsdfg_arguments(self, sdfg, cfg, dfg, state, node):
                 ptrname = cpp.ptr(out_memlet.data, desc, sdfg, self._frame)
                 defined_type, defined_ctype = self._dispatcher.defined_vars.get(ptrname, 1)
 
-                #change c type long long to opencl type long
-                if defined_ctype.__contains__("long long"):
-                    defined_ctype = defined_ctype.replace("long long", "long")
+                #change c type to opencl type
+                if defined_ctype in dtypes._CTYPES_TO_OCLTYPES:
+                    defined_ctype = dtypes._CTYPES_TO_OCLTYPES[defined_ctype]
 
                 if isinstance(desc, dace.data.Array) and (desc.storage == dtypes.StorageType.FPGA_Global
                                                           or desc.storage == dtypes.StorageType.FPGA_Local):
@@ -908,7 +911,7 @@ def allocate_view(self, sdfg: dace.SDFG, cfg: ControlFlowRegion, dfg: SDFGState,
             # derive the declaration/definition
 
             qualifier = "__global volatile "
-            atype = dtypes.pointer(nodedesc.dtype).ctype + " restrict"
+            atype = dtypes.pointer(nodedesc.dtype).ocltype + " restrict"
             aname = ptrname
             viewed_desc = sdfg.arrays[edge.data.data]
             eptr = cpp.ptr(edge.data.data, viewed_desc, sdfg, self._frame)
@@ -1261,7 +1264,7 @@ def generate_constants(self, sdfg, callsite_stream):
 
         for cstname, (csttype, cstval) in sdfg.constants_prop.items():
             if isinstance(csttype, dace.data.Array):
-                const_str = "__constant " + csttype.dtype.ctype + \
+                const_str = "__constant " + csttype.dtype.ocltype + \
                             " " + cstname + "[" + str(cstval.size) + "]"
 
                 if cstname not in self.generated_constants:
diff --git a/dace/dtypes.py b/dace/dtypes.py
index d0c6f23e03..465e73b2b1 100644
--- a/dace/dtypes.py
+++ b/dace/dtypes.py
@@ -250,12 +250,12 @@ class TilingType(aenum.AutoNumberEnum):
     numpy.int16: "short",
     numpy.int32: "int",
     numpy.intc: "int",
-    numpy.int64: "long long",
-    numpy.uint8: "unsigned char",
-    numpy.uint16: "unsigned short",
-    numpy.uint32: "unsigned int",
-    numpy.uintc: "unsigned int",
-    numpy.uint64: "unsigned long long",
+    numpy.int64: "int64_t",
+    numpy.uint8: "uint8_t",
+    numpy.uint16: "uint16_t",
+    numpy.uint32: "uint32_t",
+    numpy.uintc: "dace::uint",
+    numpy.uint64: "uint64_t",
     numpy.float16: "dace::float16",
     numpy.float32: "float",
     numpy.float64: "double",
@@ -275,17 +275,37 @@ class TilingType(aenum.AutoNumberEnum):
     numpy.int32: "int",
     numpy.intc: "int",
     numpy.int64: "long",
-    numpy.uint8: "unsigned char",
-    numpy.uint16: "unsigned short",
-    numpy.uint32: "unsigned int",
-    numpy.uint64: "unsigned long",
-    numpy.uintc: "unsigned int",
+    numpy.uint8: "uchar",
+    numpy.uint16: "ushort",
+    numpy.uint32: "uint",
+    numpy.uint64: "ulong",
+    numpy.uintc: "uint",
     numpy.float32: "float",
     numpy.float64: "double",
     numpy.complex64: "complex float",
     numpy.complex128: "complex double",
 }
 
+_CTYPES_TO_OCLTYPES = {
+    "void": "void",
+    "int": "int",
+    "float": "float",
+    "double": "double",
+    "dace::complex64": "complex float",
+    "dace::complex128": "complex double",
+    "bool": "bool",
+    "char": "char",
+    "short": "short",
+    "int": "int",
+    "int64_t": "long",
+    "uint8_t": "uchar",
+    "uint16_t": "ushort",
+    "uint32_t": "uint",
+    "dace::uint": "uint",
+    "uint64_t": "ulong",
+    "dace::float16": "half",
+}
+
 # Translation of types to OpenCL vector types
 _OCL_VECTOR_TYPES = {
     numpy.int8: "char",
@@ -1295,7 +1315,7 @@ def dtype_to_typeclass(dtype=None):
 bool = bool_
 
 TYPECLASS_TO_STRING = {
-    bool: "dace::bool",
+    bool: "dace::bool_",
     bool_: "dace::bool_",
     uint8: "dace::uint8",
     uint16: "dace::uint16",
diff --git a/dace/runtime/include/dace/reduction.h b/dace/runtime/include/dace/reduction.h
index 927bf449de..81017610ae 100644
--- a/dace/runtime/include/dace/reduction.h
+++ b/dace/runtime/include/dace/reduction.h
@@ -205,15 +205,27 @@ namespace dace {
 
 #if defined(DACE_USE_GPU_ATOMICS)
     template <>
-    struct _wcr_fixed<ReductionType::Sum, long long> {
+    struct _wcr_fixed<ReductionType::Sum, int64_t> {
        
-        static DACE_HDFI long long reduce_atomic(long long *ptr, const long long& value) {
+        static DACE_HDFI int64_t reduce_atomic(int64_t *ptr, const int64_t& value) {
             return _wcr_fixed<ReductionType::Sum, unsigned long long>::reduce_atomic((
                 unsigned long long *)ptr, 
                 static_cast<unsigned long long>(value));
         }
 
-        DACE_HDFI long long operator()(const long long &a, const long long &b) const { return a + b; }
+        DACE_HDFI int64_t operator()(const int64_t &a, const int64_t &b) const { return a + b; }
+    };
+
+    template <>
+    struct _wcr_fixed<ReductionType::Sum, uint64_t> {
+       
+        static DACE_HDFI uint64_t reduce_atomic(uint64_t *ptr, const uint64_t& value) {
+            return _wcr_fixed<ReductionType::Sum, unsigned long long>::reduce_atomic((
+                unsigned long long *)ptr, 
+                static_cast<unsigned long long>(value));
+        }
+
+        DACE_HDFI uint64_t operator()(const uint64_t &a, const uint64_t &b) const { return a + b; }
     };
 #endif
 
diff --git a/dace/runtime/include/dace/types.h b/dace/runtime/include/dace/types.h
index aa20877549..e5eed1e35e 100644
--- a/dace/runtime/include/dace/types.h
+++ b/dace/runtime/include/dace/types.h
@@ -74,6 +74,7 @@ namespace dace
     typedef uint16_t uint16;
     typedef uint32_t uint32;
     typedef uint64_t uint64;
+    typedef unsigned int uint;
     typedef float float32;
     typedef double float64;
 
diff --git a/dace/sdfg/infer_types.py b/dace/sdfg/infer_types.py
index 97010e95a7..c05708670e 100644
--- a/dace/sdfg/infer_types.py
+++ b/dace/sdfg/infer_types.py
@@ -34,9 +34,6 @@ def infer_out_connector_type(sdfg: SDFG, state: SDFGState, node: nodes.CodeNode,
     else:
         allocated_as_scalar = True
 
-    if node.out_connectors[cname].type is not None:
-        return node.out_connectors[cname].type
-
     # If nested SDFG, try to use internal array type
     if isinstance(node, nodes.NestedSDFG):
         scalar = (isinstance(node.sdfg.arrays[cname], data.Scalar) and allocated_as_scalar)
diff --git a/dace/sdfg/validation.py b/dace/sdfg/validation.py
index 1f5c263206..c603597fb1 100644
--- a/dace/sdfg/validation.py
+++ b/dace/sdfg/validation.py
@@ -244,7 +244,7 @@ def validate_sdfg(sdfg: 'dace.sdfg.SDFG', references: Set[int] = None, **context
                     warnings.warn(f'Mismatch between constant and data descriptor of "{const_name}", '
                                   f'expected to find "{const_type}" but found "{sdfg.arrays[const_name]}".')
             elif const_name in sdfg.symbols:
-                if const_type != sdfg.symbols[const_name]:
+                if const_type.dtype != sdfg.symbols[const_name]:
                     # This should actually be an error, but there is a lots of code that depends on it.
                     warnings.warn(f'Mismatch between constant and symobl type of "{const_name}", '
                                   f'expected to find "{const_type}" but found "{sdfg.symbols[const_name]}".')
diff --git a/tests/passes/dead_code_elimination_test.py b/tests/passes/dead_code_elimination_test.py
index f8920b0538..a41a11c4d6 100644
--- a/tests/passes/dead_code_elimination_test.py
+++ b/tests/passes/dead_code_elimination_test.py
@@ -254,21 +254,31 @@ def test_dce_callback_manual():
     sdfg.validate()
 
 
-def test_dce_add_type_hint_of_variable():
+@pytest.mark.parametrize('dtype', (dace.float64, dace.bool, np.float64))
+def test_dce_add_type_hint_of_variable(dtype):
     """
     The code of this test comes from this issue: https://github.com/spcl/dace/issues/1150#issue-1445418361
+    and this issue: https://github.com/spcl/dace/issues/1710
+    and this PR: https://github.com/spcl/dace/pull/1721
     """
+    if dtype is dace.bool:
+        true_value = True
+        false_value = False
+    else:
+        true_value = 3.0
+        false_value = 7.0
+
     sdfg = dace.SDFG("test")
     state = sdfg.add_state()
-    sdfg.add_array("out", dtype=dace.float64, shape=(10,))
-    sdfg.add_array("cond", dtype=dace.bool, shape=(10,))
-    sdfg.add_array("tmp", dtype=dace.float64, shape=(10,), transient=True)
+    sdfg.add_array("out", dtype=dtype, shape=(10, ))
+    sdfg.add_array("cond", dtype=dace.bool, shape=(10, ))
+    sdfg.add_array("tmp", dtype=dtype, shape=(10, ), transient=True)
     tasklet, *_ = state.add_mapped_tasklet(
-        code="""
+        code=f"""
 if _cond:
-    _tmp = 3.0
+    _tmp = {true_value}
 else:
-    _tmp = 7.0
+    _tmp = {false_value}
 _out = _tmp
         """,
         inputs={"_cond": dace.Memlet(subset="k", data="cond")},
@@ -281,14 +291,17 @@ def test_dce_add_type_hint_of_variable():
         external_edges=True,
     )
     sdfg.simplify()
-    assert tasklet.code.as_string.startswith("_tmp: dace.float64")
+    assert tasklet.code.as_string.startswith("_tmp:")
 
     compiledsdfg = sdfg.compile()
-    cond = np.random.choice(a=[True, False], size=(10,))
-    out = np.zeros((10,))
-    compiledsdfg(cond=cond, out=out)
-    assert np.all(out == np.where(cond, 3.0, 7.0))
+    cond = np.random.choice(a=[True, False], size=(10, ))
+    if isinstance(dtype, dace.typeclass):
+        out = np.zeros((10, ), dtype=dtype.as_numpy_dtype())
+    else:
+        out = np.zeros((10, ), dtype=dtype)
 
+    compiledsdfg(cond=cond, out=out)
+    assert np.all(out == np.where(cond, true_value, false_value))
 
 
 if __name__ == '__main__':
@@ -305,4 +318,6 @@ def test_dce_add_type_hint_of_variable():
     test_dce()
     test_dce_callback()
     test_dce_callback_manual()
-    test_dce_add_type_hint_of_variable()
+    test_dce_add_type_hint_of_variable(dace.float64)
+    test_dce_add_type_hint_of_variable(dace.bool)
+    test_dce_add_type_hint_of_variable(np.float64)

From 08ec5ea4f75ffa19b66c906ba12a27188b546e5a Mon Sep 17 00:00:00 2001
From: Tal Ben-Nun <tbennun@users.noreply.github.com>
Date: Fri, 8 Nov 2024 00:44:42 -0800
Subject: [PATCH 24/33] SDFG API additions for version 1.0 (#1740)

This PR adds additional API calls and fields as requested by DaCe users.
This includes:

* `SDFG.auto_optimize`
* `SDFG.regenerate_code`
* `SDFG.as_schedule_tree`
---
 dace/frontend/python/parser.py |  4 +--
 dace/sdfg/sdfg.py              | 61 +++++++++++++++++++++++++++++++++-
 2 files changed, 62 insertions(+), 3 deletions(-)

diff --git a/dace/frontend/python/parser.py b/dace/frontend/python/parser.py
index d03759fa8e..20018effd0 100644
--- a/dace/frontend/python/parser.py
+++ b/dace/frontend/python/parser.py
@@ -760,7 +760,7 @@ def _load_sdfg(self, path: str, *args, **kwargs):
 
         if sdfg is not None:
             # Set regenerate and recompile flags
-            sdfg._regenerate_code = self.regenerate_code
+            sdfg.regenerate_code = self.regenerate_code
             sdfg._recompile = self.recompile
 
         return sdfg, self._cache.make_key(argtypes, given_args, self.closure_array_keys, self.closure_constant_keys,
@@ -928,7 +928,7 @@ def _generate_pdp(self, args: Tuple[Any], kwargs: Dict[str, Any],
             # TODO: Add to parsed SDFG cache
 
             # Set regenerate and recompile flags
-            sdfg._regenerate_code = self.regenerate_code
+            sdfg.regenerate_code = self.regenerate_code
             sdfg._recompile = self.recompile
 
         return sdfg, cached
diff --git a/dace/sdfg/sdfg.py b/dace/sdfg/sdfg.py
index 3be268e44d..716bb9accc 100644
--- a/dace/sdfg/sdfg.py
+++ b/dace/sdfg/sdfg.py
@@ -38,6 +38,7 @@
     from dace.codegen.instrumentation.report import InstrumentationReport
     from dace.codegen.instrumentation.data.data_report import InstrumentedDataReport
     from dace.codegen.compiled_sdfg import CompiledSDFG
+    from dace.sdfg.analysis.schedule_tree.treenodes import ScheduleTreeScope
 
 
 class NestedDict(dict):
@@ -802,6 +803,14 @@ def start_state(self):
     def start_state(self, state_id):
         self.start_block = state_id
 
+    @property
+    def regenerate_code(self):
+        return self._regenerate_code
+
+    @regenerate_code.setter
+    def regenerate_code(self, value):
+        self._regenerate_code = value
+
     def set_global_code(self, cpp_code: str, location: str = 'frame'):
         """
         Sets C++ code that will be generated in a global scope on
@@ -1070,6 +1079,24 @@ def call_with_instrumented_data(self, dreport: 'InstrumentedDataReport', *args,
 
     ##########################################
 
+    def as_schedule_tree(self, in_place: bool = False) -> 'ScheduleTreeScope':
+        """
+        Creates a schedule tree from this SDFG and all nested SDFGs. The schedule tree is a tree of nodes that represent
+        the execution order of the SDFG.
+        Each node in the tree can either represent a single statement (symbol assignment, tasklet, copy, library node,
+        etc.) or a ``ScheduleTreeScope`` block (map, for-loop, pipeline, etc.) that contains other nodes.
+    
+        It can be used to generate code from an SDFG, or to perform schedule transformations on the SDFG. For example,
+        erasing an empty if branch, or merging two consecutive for-loops.
+
+        :param in_place: If True, the SDFG is modified in-place. Otherwise, a copy is made. Note that the SDFG might
+                         not be usable after the conversion if ``in_place`` is True!
+        :return: A schedule tree representing the given SDFG.
+        """
+        # Avoid import loop
+        from dace.sdfg.analysis.schedule_tree import sdfg_to_tree as s2t
+        return s2t.as_schedule_tree(self, in_place=in_place)
+
     @property
     def build_folder(self) -> str:
         """ Returns a relative path to the build cache folder for this SDFG. """
@@ -2293,7 +2320,7 @@ def compile(self, output_file=None, validate=True,
         ############################
         # DaCe Compilation Process #
 
-        if self._regenerate_code or not os.path.isdir(build_folder):
+        if self.regenerate_code or not os.path.isdir(build_folder):
             # Clone SDFG as the other modules may modify its contents
             sdfg = copy.deepcopy(self)
             # Fix the build folder name on the copied SDFG to avoid it changing
@@ -2463,6 +2490,38 @@ def simplify(self, validate=True, validate_all=False, verbose=False):
         from dace.transformation.passes.simplify import SimplifyPass
         return SimplifyPass(validate=validate, validate_all=validate_all, verbose=verbose).apply_pass(self, {})
 
+    def auto_optimize(self,
+                      device: dtypes.DeviceType,
+                      validate: bool = True,
+                      validate_all: bool = False,
+                      symbols: Dict[str, int] = None,
+                      use_gpu_storage: bool = False):
+        """
+        Runs a basic sequence of transformations to optimize a given SDFG to decent
+        performance. In particular, performs the following:
+            
+            * Simplify
+            * Auto-parallelization (loop-to-map)
+            * Greedy application of SubgraphFusion
+            * Tiled write-conflict resolution (MapTiling -> AccumulateTransient)
+            * Tiled stream accumulation (MapTiling -> AccumulateTransient)
+            * Collapse all maps to parallelize across all dimensions
+            * Set all library nodes to expand to ``fast`` expansion, which calls
+              the fastest library on the target device
+
+        :param device: the device to optimize for.
+        :param validate: If True, validates the SDFG after all transformations
+                         have been applied.
+        :param validate_all: If True, validates the SDFG after every step.
+        :param symbols: Optional dict that maps symbols (str/symbolic) to int/float
+        :param use_gpu_storage: If True, changes the storage of non-transient data to GPU global memory.
+        :note: Operates in-place on the given SDFG.
+        :note: This function is still experimental and may harm correctness in
+               certain cases. Please report an issue if it does.
+        """
+        from dace.transformation.auto.auto_optimize import auto_optimize
+        auto_optimize(device, validate, validate_all, symbols, use_gpu_storage)
+
     def _initialize_transformations_from_type(
         self,
         xforms: Union[Type, List[Type], 'dace.transformation.PatternTransformation'],

From 1b99fe24c7192a956c75725ec6658dab7611ebec Mon Sep 17 00:00:00 2001
From: Pratyai Mazumder <pratyai.mazumder@gmail.com>
Date: Sun, 10 Nov 2024 17:39:24 +0100
Subject: [PATCH 25/33] Replace another FORTRAN test program with `gfortran
 -Wall` certified test program. (#1736)

A follow up of #1733 that took a bit longer to figure out.

This change breaks the test on `multi_sdfg` branch, but there the
front-end is doing something additionally wrong (it somehow promotes
`nclv` into a input parameter for the whole program) -- but it will even
take longer to figure out why.
---
 tests/fortran/fortran_language_test.py | 69 +++++++++++++++-----------
 1 file changed, 40 insertions(+), 29 deletions(-)

diff --git a/tests/fortran/fortran_language_test.py b/tests/fortran/fortran_language_test.py
index 9034ba20f3..0a87baa4da 100644
--- a/tests/fortran/fortran_language_test.py
+++ b/tests/fortran/fortran_language_test.py
@@ -79,38 +79,50 @@ def test_fortran_frontend_loop1():
     """
     Tests that the loop construct is correctly parsed and translated to DaCe.
     """
-    
+
     test_string = """
-                    PROGRAM loop1_test
-                    implicit none
-                    double precision d(3,4,5)
-                    CALL loop1_test_function(d)
-                    end
+program loop1_test
+  implicit none
+  logical :: d(3, 4, 5)
+  call loop1_test_function(d)
+end
 
-                    SUBROUTINE loop1_test_function(d)
-                   double precision d(3,4,5),ZFAC(10)
-                   INTEGER :: a, JK, JL,JM
-                   INTEGER, PARAMETER :: KLEV=10, N=10,NCLV=3
-
-                   double precision :: RLMIN,ZVQX(NCLV)
-                   LOGICAL :: LLCOOLJ,LLFALL(NCLV)
-                   LLFALL(:)= .FALSE.
-                   ZVQX(:)= 0.0
-                   ZVQX(2)= 1.0
-                   DO JM=1,NCLV
-                    IF (ZVQX(JM)>0.0) LLFALL(JM)=.TRUE. ! falling species
-                   ENDDO
-
-                   d(1,1,1)=LLFALL(1)
-                   d(1,1,2)=LLFALL(2)                 
-                   END SUBROUTINE loop1_test_function
-                    """
+subroutine loop1_test_function(d)
+  logical :: d(3, 4, 5), ZFAC(10)
+  integer :: a, JK, JL, JM
+  integer, parameter :: KLEV = 10, N = 10, NCLV = 3
+  integer :: tmp
+
+  double precision :: RLMIN, ZVQX(NCLV)
+  logical :: LLCOOLJ, LLFALL(NCLV)
+  LLFALL(:) = .false.
+  ZVQX(:) = 0.0
+  ZVQX(2) = 1.0
+  do JM = 1, NCLV
+    if (ZVQX(JM) > 0.0) LLFALL(JM) = .true. ! falling species
+  end do
+
+  do I = 1, 3
+    do J = 1, 4
+      do K = 1, 5
+        tmp = I+J+K-3
+        tmp = mod(tmp, 2)
+        if (tmp == 1) then
+          d(I, J, K) = LLFALL(2)
+        else
+          d(I, J, K) = LLFALL(1)
+        end if
+      end do
+    end do
+  end do
+end subroutine loop1_test_function
+"""
     sdfg = fortran_parser.create_sdfg_from_string(test_string, "loop1_test")
     sdfg.simplify(verbose=True)
-    d = np.full([3, 4, 5], 42, order="F", dtype=np.float64)
+    d = np.full([3, 4, 5], 42, order="F", dtype=np.int32)
     sdfg(d=d)
-    assert (d[0, 0, 0] == 0)
-    assert (d[0, 0, 1] == 1)
+    # Verify the checkerboard pattern.
+    assert all(bool(v) == ((i+j+k) % 2 == 1) for (i, j, k), v in np.ndenumerate(d))
 
 
 def test_fortran_frontend_function_statement1():
@@ -184,7 +196,7 @@ def test_fortran_frontend_pow2():
     """
     Tests that the power intrinsic is correctly parsed and translated to DaCe (this time it's p sqrt p).
     """
-    
+
     test_string = """
                     PROGRAM pow2_test
                     implicit none
@@ -241,7 +253,6 @@ def test_fortran_frontend_sign1():
 
 
 if __name__ == "__main__":
-
     test_fortran_frontend_real_kind_selector()
     test_fortran_frontend_if1()
     test_fortran_frontend_loop1()

From cb6391f7bfbc7c84661cfc5733b6ad6c79635c52 Mon Sep 17 00:00:00 2001
From: Tal Ben-Nun <tbennun@users.noreply.github.com>
Date: Mon, 11 Nov 2024 01:44:09 -0800
Subject: [PATCH 26/33] Unskip unit tests and provide reasons for skipped tests
 (#1742)

* Brings back 36 tests that were skipped due to prior regressions that
are now fixed.
* Fixes codegen generating non-atomic WCR w.r.t. neighboring edges
* Contains minor modifications that were used to unskip certain tests
(e.g., use of the no-longer-existent `symbol.get()` method)
* Gives valid reasons for all other skipped tests
---
 .github/workflows/general-ci.yml              |  2 +-
 dace/codegen/compiled_sdfg.py                 |  2 +-
 dace/codegen/targets/cpp.py                   | 42 ++++++++++++++----
 dace/sdfg/sdfg.py                             |  2 +-
 dace/subsets.py                               |  4 ++
 pytest.ini                                    |  1 +
 samples/fpga/jacobi_fpga_systolic.py          |  6 +--
 tests/codegen/allocation_lifetime_test.py     |  2 +-
 tests/fpga/jacobi_fpga_test.py                |  4 +-
 .../map_unroll_processing_elements_test.py    |  5 ++-
 tests/fpga/matmul_test.py                     |  6 ++-
 tests/fpga/streaming_memory_test.py           | 36 ++++++++--------
 tests/fpga/vec_sum_test.py                    |  6 +--
 tests/inlining_test.py                        |  4 +-
 tests/instrumentation_test.py                 |  3 +-
 ...ledtest.py => nested_control_flow_test.py} |  5 +--
 .../npbench/deep_learning/conv2d_bias_test.py |  2 +-
 tests/npbench/deep_learning/lenet_test.py     |  2 +-
 tests/npbench/misc/azimint_naive_test.py      |  2 +-
 tests/npbench/misc/contour_integral_test.py   |  7 ++-
 tests/npbench/misc/mandelbrot1_test.py        |  6 +--
 tests/npbench/misc/mandelbrot2_test.py        |  6 +--
 tests/npbench/misc/nbody_test.py              |  2 +-
 tests/npbench/misc/spmv_test.py               |  2 +-
 tests/npbench/misc/stockham_fft_test.py       |  4 +-
 tests/npbench/polybench/correlation_test.py   |  1 -
 tests/npbench/polybench/deriche_test.py       |  1 -
 tests/npbench/polybench/doitgen_test.py       |  1 -
 tests/npbench/polybench/durbin_test.py        |  1 -
 tests/npbench/polybench/gemver_test.py        |  1 -
 tests/npbench/polybench/symm_test.py          |  1 -
 tests/npbench/weather_stencils/vadv_test.py   |  3 +-
 tests/numpy/linalg_test.py                    |  6 +--
 tests/numpy/list_globals_test.py              |  2 +-
 tests/numpy/transpose_test.py                 |  2 +-
 tests/numpy/ufunc_test.py                     | 43 ++++---------------
 .../assignment_statements_test.py             |  4 +-
 tests/python_frontend/augassign_wcr_test.py   | 11 ++---
 .../callback_autodetect_test.py               |  8 ++--
 .../conditional_assignment_test.py            |  2 +-
 tests/python_frontend/lambda_test.py          | 10 ++---
 tests/python_frontend/string_test.py          |  4 +-
 .../structures/structure_python_test.py       |  2 +-
 tests/reduce_strided_disabledtest.py          | 38 ++++++++--------
 tests/rtl/hardware_test.py                    | 10 ++---
 tests/sdfg/scalar_return.py                   |  4 +-
 tests/symbol_dependent_transients_test.py     |  4 +-
 47 files changed, 159 insertions(+), 163 deletions(-)
 rename tests/{nested_control_flow_disabledtest.py => nested_control_flow_test.py} (88%)

diff --git a/.github/workflows/general-ci.yml b/.github/workflows/general-ci.yml
index 2044639e5f..cde07f0406 100644
--- a/.github/workflows/general-ci.yml
+++ b/.github/workflows/general-ci.yml
@@ -55,7 +55,7 @@ jobs:
         else
             export DACE_optimizer_automatic_simplification=${{ matrix.simplify }}
         fi
-        pytest -n auto --cov-report=xml --cov=dace --tb=short -m "not gpu and not verilator and not tensorflow and not mkl and not sve and not papi and not mlir and not lapack and not fpga and not mpi and not rtl_hardware and not scalapack and not datainstrument"
+        pytest -n auto --cov-report=xml --cov=dace --tb=short -m "not gpu and not verilator and not tensorflow and not mkl and not sve and not papi and not mlir and not lapack and not fpga and not mpi and not rtl_hardware and not scalapack and not datainstrument and not long"
         ./codecov
 
     - name: Test OpenBLAS LAPACK
diff --git a/dace/codegen/compiled_sdfg.py b/dace/codegen/compiled_sdfg.py
index 332db028ae..bae8531e62 100644
--- a/dace/codegen/compiled_sdfg.py
+++ b/dace/codegen/compiled_sdfg.py
@@ -580,7 +580,7 @@ def _construct_args(self, kwargs) -> Tuple[Tuple[Any], Tuple[Any]]:
         arg_ctypes = tuple(at.dtype.as_ctypes() for at in argtypes)
 
         constants = self.sdfg.constants
-        callparams = tuple((actype(arg.get()) if isinstance(arg, symbolic.symbol) else arg, actype, atype, aname)
+        callparams = tuple((arg, actype, atype, aname)
                            for arg, actype, atype, aname in zip(arglist, arg_ctypes, argtypes, argnames)
                            if not (symbolic.issymbolic(arg) and (hasattr(arg, 'name') and arg.name in constants)))
 
diff --git a/dace/codegen/targets/cpp.py b/dace/codegen/targets/cpp.py
index 911a792ac9..89239abcb3 100644
--- a/dace/codegen/targets/cpp.py
+++ b/dace/codegen/targets/cpp.py
@@ -26,7 +26,7 @@
 from dace.frontend import operations
 from dace.frontend.python import astutils
 from dace.frontend.python.astutils import ExtNodeTransformer, rname, unparse
-from dace.sdfg import nodes, graph as gr, utils
+from dace.sdfg import nodes, graph as gr, utils, propagation
 from dace.properties import LambdaProperty
 from dace.sdfg import SDFG, is_devicelevel_gpu, SDFGState
 from dace.codegen.targets import fpga
@@ -713,6 +713,31 @@ def _check_map_conflicts(map, edge):
     return True
 
 
+def _check_neighbor_conflicts(dfg, edge):
+    """
+    Checks for other memlets writing to edges that may overlap in subsets.
+
+    Returns True if there are no conflicts, False if there may be.
+    """
+    outer = propagation.propagate_memlet(dfg, edge.data, edge.dst, False)
+    siblings = dfg.in_edges(edge.dst)
+    for sibling in siblings:
+        if sibling is edge:
+            continue
+        if sibling.data.data != edge.data.data:
+            continue
+        # Check if there is definitely no overlap in the propagated memlet
+        sibling_outer = propagation.propagate_memlet(dfg, sibling.data, edge.dst, False)
+        if subsets.intersects(outer.subset, sibling_outer.subset) == False:
+            # In that case, continue
+            continue
+
+        # Other cases are indeterminate and will be atomic
+        return False
+    # No overlaps in current scope
+    return True
+
+
 def write_conflicted_map_params(map, edge):
     result = []
     for itervar, (_, _, mapskip) in zip(map.params, map.range):
@@ -769,6 +794,8 @@ def is_write_conflicted_with_reason(dfg, edge, datanode=None, sdfg_schedule=None
         for e in path:
             if (isinstance(e.dst, nodes.ExitNode) and (e.dst.map.schedule != dtypes.ScheduleType.Sequential
                                                        and e.dst.map.schedule != dtypes.ScheduleType.Snitch)):
+                if not _check_neighbor_conflicts(dfg, e):
+                    return e.dst
                 if _check_map_conflicts(e.dst.map, e):
                     # This map is parallel w.r.t. WCR
                     # print('PAR: Continuing from map')
@@ -984,10 +1011,9 @@ def unparse_tasklet(sdfg, cfg, state_id, dfg, node, function_stream, callsite_st
     # To prevent variables-redefinition, build dictionary with all the previously defined symbols
     defined_symbols = state_dfg.symbols_defined_at(node)
 
-    defined_symbols.update({
-        k: v.dtype if hasattr(v, 'dtype') else dtypes.typeclass(type(v))
-        for k, v in sdfg.constants.items()
-    })
+    defined_symbols.update(
+        {k: v.dtype if hasattr(v, 'dtype') else dtypes.typeclass(type(v))
+         for k, v in sdfg.constants.items()})
 
     for connector, (memlet, _, _, conntype) in memlets.items():
         if connector is not None:
@@ -1038,7 +1064,7 @@ def _Name(self, t: ast.Name):
         # Replace values with their code-generated names (for example, persistent arrays)
         desc = self.sdfg.arrays[t.id]
         self.write(ptr(t.id, desc, self.sdfg, self.codegen))
-    
+
     def _Attribute(self, t: ast.Attribute):
         from dace.frontend.python.astutils import rname
         name = rname(t)
@@ -1325,8 +1351,8 @@ def visit_BinOp(self, node: ast.BinOp):
                 evaluated_constant = symbolic.evaluate(unparsed, self.constants)
                 evaluated = symbolic.symstr(evaluated_constant, cpp_mode=True)
                 value = ast.parse(evaluated).body[0].value
-                if isinstance(evaluated_node, numbers.Number) and evaluated_node != (value.value if sys.version_info
-                                                                                     >= (3, 8) else value.n):
+                if isinstance(evaluated_node, numbers.Number) and evaluated_node != (value.value if sys.version_info >=
+                                                                                     (3, 8) else value.n):
                     raise TypeError
                 node.right = ast.parse(evaluated).body[0].value
             except (TypeError, AttributeError, NameError, KeyError, ValueError, SyntaxError):
diff --git a/dace/sdfg/sdfg.py b/dace/sdfg/sdfg.py
index 716bb9accc..1b449403d5 100644
--- a/dace/sdfg/sdfg.py
+++ b/dace/sdfg/sdfg.py
@@ -1208,7 +1208,7 @@ def cast(dtype: dt.Data, value: Any):
             if isinstance(dtype, dt.Array):
                 return value
             elif isinstance(dtype, dt.Scalar):
-                return dtype.dtype(value)
+                return dtype.dtype.type(value)
             raise TypeError('Unsupported data type %s' % dtype)
 
         result.update({k: cast(*v) for k, v in self.constants_prop.items()})
diff --git a/dace/subsets.py b/dace/subsets.py
index 0fa6fb536c..0fdc36c22e 100644
--- a/dace/subsets.py
+++ b/dace/subsets.py
@@ -404,6 +404,8 @@ def data_dims(self):
                                                                                        for ts in self.tile_sizes))
 
     def offset(self, other, negative, indices=None, offset_end=True):
+        if other is None:
+            return
         if not isinstance(other, Subset):
             if isinstance(other, (list, tuple)):
                 other = Indices(other)
@@ -420,6 +422,8 @@ def offset(self, other, negative, indices=None, offset_end=True):
             self.ranges[i] = (rb + mult * off[i], re, rs)
 
     def offset_new(self, other, negative, indices=None, offset_end=True):
+        if other is None:
+            return Range(self.ranges)
         if not isinstance(other, Subset):
             if isinstance(other, (list, tuple)):
                 other = Indices(other)
diff --git a/pytest.ini b/pytest.ini
index 087be3d897..e36c6cecbd 100644
--- a/pytest.ini
+++ b/pytest.ini
@@ -14,6 +14,7 @@ markers =
     scalapack: Test requires ScaLAPACK (Intel MKL and OpenMPI). (select with '-m scalapack')
     datainstrument: Test uses data instrumentation (select with '-m datainstrument')
     hptt: Test requires the HPTT library (select with '-m "hptt')
+    long: Test runs for a long time and is skipped in CI (select with '-m "long"')
 python_files =
     *_test.py
     *_cudatest.py
diff --git a/samples/fpga/jacobi_fpga_systolic.py b/samples/fpga/jacobi_fpga_systolic.py
index d022f6712b..503f766056 100644
--- a/samples/fpga/jacobi_fpga_systolic.py
+++ b/samples/fpga/jacobi_fpga_systolic.py
@@ -276,10 +276,10 @@ def run_jacobi(w: int, h: int, t: int, p: int, specialize_all: bool = False):
         print("Specializing H and T...")
 
     jacobi = make_sdfg(specialize_all, h, w, t, p)
-    jacobi.specialize(dict(W=W, P=P))
+    jacobi.specialize(dict(W=w, P=p))
 
     if specialize_all:
-        jacobi.specialize(dict(H=H, T=T))
+        jacobi.specialize(dict(H=h, T=t))
 
     if t % p != 0:
         raise ValueError("Iteration must be divisable by number of processing elements")
@@ -301,7 +301,7 @@ def run_jacobi(w: int, h: int, t: int, p: int, specialize_all: bool = False):
     if specialize_all:
         jacobi(A=A)
     else:
-        jacobi(A=A, H=H, T=T)
+        jacobi(A=A, H=h, T=t)
 
     # Regression
     kernel = np.array([[0, 0.2, 0], [0.2, 0.2, 0.2], [0, 0.2, 0]], dtype=np.float32)
diff --git a/tests/codegen/allocation_lifetime_test.py b/tests/codegen/allocation_lifetime_test.py
index 9a68cd2140..380367057a 100644
--- a/tests/codegen/allocation_lifetime_test.py
+++ b/tests/codegen/allocation_lifetime_test.py
@@ -480,7 +480,7 @@ def test_branched_allocation(mode):
     sdfg.compile()
 
 
-@pytest.mark.skip
+@pytest.mark.skip('Dynamic array resize is not yet supported')
 def test_scope_multisize():
     """ An array that needs to be allocated multiple times with different sizes. """
     sdfg = dace.SDFG('test')
diff --git a/tests/fpga/jacobi_fpga_test.py b/tests/fpga/jacobi_fpga_test.py
index 0821e95ed6..290eccaaf7 100644
--- a/tests/fpga/jacobi_fpga_test.py
+++ b/tests/fpga/jacobi_fpga_test.py
@@ -6,8 +6,8 @@
 
 # This kernel does not work with the Intel FPGA codegen, because it uses the
 # constant systolic array index in the connector on the nested SDFG.
-@pytest.mark.skip
-@xilinx_test()
+@pytest.mark.skip('Xilinx failure due to unresolved phi nodes, Intel FPGA failure due to systolic array index')
+@xilinx_test(assert_ii_1=False)
 def test_jacobi_fpga():
     jacobi = import_sample(Path("fpga") / "jacobi_fpga_systolic.py")
     return jacobi.run_jacobi(64, 512, 16, 4)
diff --git a/tests/fpga/map_unroll_processing_elements_test.py b/tests/fpga/map_unroll_processing_elements_test.py
index de73997f1b..069ab47e04 100644
--- a/tests/fpga/map_unroll_processing_elements_test.py
+++ b/tests/fpga/map_unroll_processing_elements_test.py
@@ -9,7 +9,7 @@
 from dace.config import set_temporary
 
 
-@pytest.mark.skip
+@pytest.mark.skip('Xilinx HLS fails due to unresolved phi nodes')
 @xilinx_test(assert_ii_1=False)
 def test_map_unroll_processing_elements():
     # Grab the systolic GEMM implementation the samples directory
@@ -56,7 +56,7 @@ def test_map_unroll_processing_elements():
     return sdfg
 
 
-@pytest.mark.skip
+@pytest.mark.skip('Test no longer achieves II=1')
 @xilinx_test(assert_ii_1=True)
 def test_map_unroll_processing_elements_decoupled():
     # Grab the systolic GEMM implementation the samples directory
@@ -105,3 +105,4 @@ def test_map_unroll_processing_elements_decoupled():
 
 if __name__ == "__main__":
     test_map_unroll_processing_elements(None)
+    test_map_unroll_processing_elements_decoupled(None)
diff --git a/tests/fpga/matmul_test.py b/tests/fpga/matmul_test.py
index da7d3d2dfc..524672433f 100644
--- a/tests/fpga/matmul_test.py
+++ b/tests/fpga/matmul_test.py
@@ -162,7 +162,7 @@ def test_gemm_vectorized():
     return sdfg
 
 
-@pytest.mark.skip
+@pytest.mark.skip('Xilinx HLS fails due to unresolved phi nodes')
 @xilinx_test(assert_ii_1=True)
 def test_gemm_vectorized_decoupled():
     # Test with vectorization
@@ -201,7 +201,7 @@ def test_gemm_size_not_multiples_of():
     return sdfg
 
 
-@pytest.mark.skip
+@pytest.mark.skip('Xilinx HLS fails due to unresolved phi nodes')
 @xilinx_test()
 def test_gemm_size_not_multiples_of_decoupled():
     # Test with matrix sizes that are not a multiple of #PEs and Tile sizes
@@ -249,5 +249,7 @@ def matmul_np(A: dace.float64[128, 64], B: dace.float64[64, 32], C: dace.float64
     test_naive_matmul_fpga(None)
     test_systolic_matmul_fpga(None)
     test_gemm_vectorized(None)
+    test_gemm_vectorized_decoupled(None)
     test_gemm_size_not_multiples_of(None)
+    test_gemm_size_not_multiples_of_decoupled(None)
     test_matmul_np(None)
diff --git a/tests/fpga/streaming_memory_test.py b/tests/fpga/streaming_memory_test.py
index 0a75ce53f8..11a56c42f4 100644
--- a/tests/fpga/streaming_memory_test.py
+++ b/tests/fpga/streaming_memory_test.py
@@ -380,7 +380,7 @@ def test_streaming_and_composition():
     return sdfg
 
 
-@pytest.mark.skip(reason="Save time")
+@pytest.mark.long
 def test_mem_buffer_vec_add_1():
     # Make SDFG
     sdfg: dace.SDFG = vecadd_1_streaming.to_sdfg()
@@ -408,7 +408,7 @@ def test_mem_buffer_vec_add_1():
     return sdfg
 
 
-@pytest.mark.skip(reason="Save time")
+@pytest.mark.long
 def test_mem_buffer_vec_add_1_symbolic():
     # Make SDFG
     sdfg: dace.SDFG = vecadd_1_streaming_symbol.to_sdfg()
@@ -495,55 +495,55 @@ def mem_buffer_vec_add_types(dace_type0, dace_type1, dace_type2, np_type0, np_ty
     return sdfg
 
 
-@pytest.mark.skip(reason="Save time")
+@pytest.mark.long
 # def test_mem_buffer_vec_add_float16():
 #     return mem_buffer_vec_add_types(dace.float16, dace.float16, dace.float16, np.float16, np.float16, np.float16)
-@pytest.mark.skip(reason="Save time")
+@pytest.mark.long
 def test_mem_buffer_vec_add_float32():
     return mem_buffer_vec_add_types(dace.float32, dace.float32, dace.float32, np.float32, np.float32, np.float32)
 
 
-@pytest.mark.skip(reason="Save time")
+@pytest.mark.long
 def test_mem_buffer_vec_add_float64():
     return mem_buffer_vec_add_types(dace.float64, dace.float64, dace.float64, np.float64, np.float64, np.float64)
 
 
-@pytest.mark.skip(reason="Save time")
+@pytest.mark.long
 def test_mem_buffer_vec_add_int8():
     return mem_buffer_vec_add_types(dace.int8, dace.int8, dace.int8, np.int8, np.int8, np.int8)
 
 
-@pytest.mark.skip(reason="Save time")
+@pytest.mark.long
 def test_mem_buffer_vec_add_int16():
     return mem_buffer_vec_add_types(dace.int16, dace.int16, dace.int16, np.int16, np.int16, np.int16)
 
 
-@pytest.mark.skip(reason="Save time")
+@pytest.mark.long
 def test_mem_buffer_vec_add_int32():
     return mem_buffer_vec_add_types(dace.int32, dace.int32, dace.int32, np.int32, np.int32, np.int32)
 
 
-@pytest.mark.skip(reason="Save time")
+@pytest.mark.long
 def test_mem_buffer_vec_add_int64():
     return mem_buffer_vec_add_types(dace.int64, dace.int64, dace.int64, np.int64, np.int64, np.int64)
 
 
-@pytest.mark.skip(reason="Save time")
+@pytest.mark.long
 def test_mem_buffer_vec_add_complex64():
     return mem_buffer_vec_add_types(dace.complex64, dace.complex64, dace.complex64, np.complex64, np.complex64,
                                     np.complex64)
 
 
-@pytest.mark.skip(reason="Save time")
+@pytest.mark.long
 def test_mem_buffer_vec_add_complex128():
     return mem_buffer_vec_add_types(dace.complex128, dace.complex128, dace.complex128, np.complex128, np.complex128,
                                     np.complex128)
 
 
-@pytest.mark.skip(reason="Save time")
+@pytest.mark.long
 # def test_mem_buffer_vec_add_mixed_float():
 #     return mem_buffer_vec_add_types(dace.float16, dace.float32, dace.float64, np.float16, np.float32, np.float64)
-@pytest.mark.skip(reason="Save time")
+@pytest.mark.long
 def test_mem_buffer_vec_add_mixed_int():
     return mem_buffer_vec_add_types(dace.int16, dace.int32, dace.int64, np.int16, np.int32, np.int64)
 
@@ -575,7 +575,7 @@ def test_mem_buffer_mat_add():
     return sdfg
 
 
-@pytest.mark.skip(reason="Save time")
+@pytest.mark.long
 def test_mem_buffer_mat_add_symbol():
     # Make SDFG
     sdfg: dace.SDFG = matadd_streaming_symbol.to_sdfg()
@@ -602,7 +602,7 @@ def test_mem_buffer_mat_add_symbol():
     return sdfg
 
 
-@pytest.mark.skip(reason="Save time")
+@pytest.mark.long
 def test_mem_buffer_tensor_add():
     # Make SDFG
     sdfg: dace.SDFG = tensoradd_streaming.to_sdfg()
@@ -688,7 +688,7 @@ def test_mem_buffer_multistream_with_deps():
     return sdfg
 
 
-@pytest.mark.skip(reason="Save time")
+@pytest.mark.long
 def test_mem_buffer_mat_mul():
     # Make SDFG
     sdfg: dace.SDFG = matmul_streaming.to_sdfg()
@@ -799,7 +799,7 @@ def test_mem_buffer_not_applicable():
     return []
 
 
-@pytest.mark.skip(reason="Save time")
+@pytest.mark.long
 def test_mem_buffer_atax():
 
     A = np.random.rand(M, N).astype(np.float32)
@@ -843,7 +843,7 @@ def test_mem_buffer_atax():
     return sdfg
 
 
-@pytest.mark.skip(reason="Save time")
+@pytest.mark.long
 def test_mem_buffer_bicg():
 
     A = np.random.rand(N, M).astype(np.float32)
diff --git a/tests/fpga/vec_sum_test.py b/tests/fpga/vec_sum_test.py
index f6817985c9..791ba80e5d 100644
--- a/tests/fpga/vec_sum_test.py
+++ b/tests/fpga/vec_sum_test.py
@@ -83,16 +83,16 @@ def test_vec_sum_vectorize_first_decoupled_interfaces():
         return run_vec_sum(True)
 
 
-@pytest.mark.skip
 @xilinx_test(assert_ii_1=True)
 def test_vec_sum_fpga_transform_first_decoupled_interfaces():
     # For this test, decoupled read/write interfaces are needed to achieve II=1
     with set_temporary("compiler", "xilinx", "decouple_array_interfaces", value=True):
-        return run_vec_sum(True)
+        with set_temporary('testing', 'serialization', value=False):
+            return run_vec_sum(True)
 
 
 if __name__ == "__main__":
     test_vec_sum_vectorize_first(None)
     test_vec_sum_fpga_transform_first(None)
-
+    test_vec_sum_fpga_transform_first_decoupled_interfaces(None)
     
diff --git a/tests/inlining_test.py b/tests/inlining_test.py
index c6d8fa8d9f..251c85e7bc 100644
--- a/tests/inlining_test.py
+++ b/tests/inlining_test.py
@@ -42,7 +42,7 @@ def test():
     myprogram.compile(dace.float32[W, H], dace.float32[H, W], dace.int32)
 
 
-@pytest.mark.skip
+@pytest.mark.skip('CI failure that cannot be reproduced outside CI')
 def test_regression_reshape_unsqueeze():
     nsdfg = dace.SDFG("nested_reshape_node")
     nstate = nsdfg.add_state()
@@ -456,7 +456,7 @@ def test(A: dace.float64[96, 32], B: dace.float64[42, 32]):
 
 if __name__ == "__main__":
     test()
-    # Skipped to to bug that cannot be reproduced
+    # Skipped due to bug that cannot be reproduced outside CI
     # test_regression_reshape_unsqueeze()
     test_empty_memlets()
     test_multistate_inline()
diff --git a/tests/instrumentation_test.py b/tests/instrumentation_test.py
index 69eff85a8e..2aa26edf36 100644
--- a/tests/instrumentation_test.py
+++ b/tests/instrumentation_test.py
@@ -62,8 +62,7 @@ def test_timer():
     onetest(dace.InstrumentationType.Timer)
 
 
-#@pytest.mark.papi
-@pytest.mark.skip
+@pytest.mark.papi
 def test_papi():
     # Run a lighter load for the sake of performance
     onetest(dace.InstrumentationType.PAPI_Counters, 4)
diff --git a/tests/nested_control_flow_disabledtest.py b/tests/nested_control_flow_test.py
similarity index 88%
rename from tests/nested_control_flow_disabledtest.py
rename to tests/nested_control_flow_test.py
index 994b756d51..215a6afb90 100644
--- a/tests/nested_control_flow_disabledtest.py
+++ b/tests/nested_control_flow_test.py
@@ -22,8 +22,7 @@ def nested_cflow_test(A: dace.int32[1]):
                             out_a = in_a + 2
 
 
-@pytest.mark.skip
-def test():
+def test_nested_control_flow_with_explicit_tasklets():
     A = np.zeros(1).astype(np.int32)
     nested_cflow_test(A)
 
@@ -33,4 +32,4 @@ def test():
 
 
 if __name__ == "__main__":
-    test()
+    test_nested_control_flow_with_explicit_tasklets()
diff --git a/tests/npbench/deep_learning/conv2d_bias_test.py b/tests/npbench/deep_learning/conv2d_bias_test.py
index 7d9f1a60b0..648903ffb9 100644
--- a/tests/npbench/deep_learning/conv2d_bias_test.py
+++ b/tests/npbench/deep_learning/conv2d_bias_test.py
@@ -111,7 +111,7 @@ def test_cpu():
     run_conv2d_bias(dace.dtypes.DeviceType.CPU)
 
 
-@pytest.mark.skip
+@pytest.mark.skip('Illegal memory access error')
 # @pytest.mark.gpu
 def test_gpu():
     run_conv2d_bias(dace.dtypes.DeviceType.GPU)
diff --git a/tests/npbench/deep_learning/lenet_test.py b/tests/npbench/deep_learning/lenet_test.py
index a1ec02528a..37cba9af9b 100644
--- a/tests/npbench/deep_learning/lenet_test.py
+++ b/tests/npbench/deep_learning/lenet_test.py
@@ -201,7 +201,7 @@ def test_cpu(monkeypatch):
     run_lenet(dace.dtypes.DeviceType.CPU)
 
 
-@pytest.mark.skip(reason="Code error")
+@pytest.mark.skip(reason="std::runtime_error")
 @pytest.mark.gpu
 def test_gpu():
     run_lenet(dace.dtypes.DeviceType.GPU)
diff --git a/tests/npbench/misc/azimint_naive_test.py b/tests/npbench/misc/azimint_naive_test.py
index 522b545f4c..c1938fce97 100644
--- a/tests/npbench/misc/azimint_naive_test.py
+++ b/tests/npbench/misc/azimint_naive_test.py
@@ -98,7 +98,7 @@ def test_gpu():
     run_azimint_naive(dace.dtypes.DeviceType.GPU)
 
 
-@pytest.mark.skip(reason="Validation error")
+@pytest.mark.skip(reason="Incorrect output")
 @fpga_test(assert_ii_1=False)
 def test_fpga():
     run_azimint_naive(dace.dtypes.DeviceType.FPGA)
diff --git a/tests/npbench/misc/contour_integral_test.py b/tests/npbench/misc/contour_integral_test.py
index 4477e392a0..02e1629b76 100644
--- a/tests/npbench/misc/contour_integral_test.py
+++ b/tests/npbench/misc/contour_integral_test.py
@@ -113,9 +113,8 @@ def test_cpu():
     run_contour_integral(dace.dtypes.DeviceType.CPU)
 
 
-# NOTE: Doesn't work yet with GPU-auto-optimize
-# @pytest.mark.gpu
-@pytest.mark.skip
+@pytest.mark.gpu
+@pytest.mark.skip('Incorrect outputs due to auto-optimize')
 def test_gpu():
     run_contour_integral(dace.dtypes.DeviceType.GPU)
 
@@ -139,4 +138,4 @@ def test_fpga():
     elif target == "gpu":
         run_contour_integral(dace.dtypes.DeviceType.GPU)
     elif target == "fpga":
-        run_contour_integral(dace.dtypes.DeviceType.FPGA)
\ No newline at end of file
+        run_contour_integral(dace.dtypes.DeviceType.FPGA)
diff --git a/tests/npbench/misc/mandelbrot1_test.py b/tests/npbench/misc/mandelbrot1_test.py
index 13ee414c34..521d41c560 100644
--- a/tests/npbench/misc/mandelbrot1_test.py
+++ b/tests/npbench/misc/mandelbrot1_test.py
@@ -103,18 +103,18 @@ def run_mandelbrot1(device_type: dace.dtypes.DeviceType):
     return sdfg
 
 
-@pytest.mark.skip(reason="Parsing error")
+@pytest.mark.skip(reason="Parsing error (see issue #1139)")
 def test_cpu():
     run_mandelbrot1(dace.dtypes.DeviceType.CPU)
 
 
-@pytest.mark.skip(reason="Parsing error")
+@pytest.mark.skip(reason="Parsing error (see issue #1139)")
 @pytest.mark.gpu
 def test_gpu():
     run_mandelbrot1(dace.dtypes.DeviceType.GPU)
 
 
-@pytest.mark.skip(reason="Parsing error")
+@pytest.mark.skip(reason="Parsing error (see issue #1139)")
 @fpga_test(assert_ii_1=False)
 def test_fpga():
     return run_mandelbrot1(dace.dtypes.DeviceType.FPGA)
diff --git a/tests/npbench/misc/mandelbrot2_test.py b/tests/npbench/misc/mandelbrot2_test.py
index 8d775155b7..aaca2c6db9 100644
--- a/tests/npbench/misc/mandelbrot2_test.py
+++ b/tests/npbench/misc/mandelbrot2_test.py
@@ -151,18 +151,18 @@ def run_mandelbrot2(device_type: dace.dtypes.DeviceType):
     return sdfg
 
 
-@pytest.mark.skip(reason="Parsing error")
+@pytest.mark.skip(reason="Parsing error (see issue #1139)")
 def test_cpu():
     run_mandelbrot2(dace.dtypes.DeviceType.CPU)
 
 
-@pytest.mark.skip(reason="Parsing error")
+@pytest.mark.skip(reason="Parsing error (see issue #1139)")
 @pytest.mark.gpu
 def test_gpu():
     run_mandelbrot2(dace.dtypes.DeviceType.GPU)
 
 
-@pytest.mark.skip(reason="Parsing error")
+@pytest.mark.skip(reason="Parsing error (see issue #1139)")
 @fpga_test(assert_ii_1=False)
 def test_fpga():
     return run_mandelbrot2(dace.dtypes.DeviceType.FPGA)
diff --git a/tests/npbench/misc/nbody_test.py b/tests/npbench/misc/nbody_test.py
index e0b320b119..436677ad63 100644
--- a/tests/npbench/misc/nbody_test.py
+++ b/tests/npbench/misc/nbody_test.py
@@ -304,7 +304,7 @@ def test_cpu():
     run_nbody(dace.dtypes.DeviceType.CPU)
 
 
-@pytest.mark.skip(reason="Compiler error")
+@pytest.mark.skip(reason="Incorrect output")
 @pytest.mark.gpu
 def test_gpu():
     run_nbody(dace.dtypes.DeviceType.GPU)
diff --git a/tests/npbench/misc/spmv_test.py b/tests/npbench/misc/spmv_test.py
index 549aea65dd..0771ff5198 100644
--- a/tests/npbench/misc/spmv_test.py
+++ b/tests/npbench/misc/spmv_test.py
@@ -122,4 +122,4 @@ def test_fpga():
     elif target == "gpu":
         run_spmv(dace.dtypes.DeviceType.GPU)
     elif target == "fpga":
-        run_spmv(dace.dtypes.DeviceType.FPGA)
\ No newline at end of file
+        run_spmv(dace.dtypes.DeviceType.FPGA)
diff --git a/tests/npbench/misc/stockham_fft_test.py b/tests/npbench/misc/stockham_fft_test.py
index 5cf1cf8e54..8fc5e88203 100644
--- a/tests/npbench/misc/stockham_fft_test.py
+++ b/tests/npbench/misc/stockham_fft_test.py
@@ -155,12 +155,12 @@ def run_stockham_fft(device_type: dace.dtypes.DeviceType):
     return sdfg
 
 
-@pytest.mark.skip(reason="Error in expansion")
+@pytest.mark.skip(reason="Assertion error in read_and_write_sets")
 def test_cpu():
     run_stockham_fft(dace.dtypes.DeviceType.CPU)
 
 
-@pytest.mark.skip(reason="Runtime error")
+@pytest.mark.skip(reason="Assertion error in read_and_write_sets")
 @pytest.mark.gpu
 def test_gpu():
     run_stockham_fft(dace.dtypes.DeviceType.GPU)
diff --git a/tests/npbench/polybench/correlation_test.py b/tests/npbench/polybench/correlation_test.py
index d1536d51c8..d743ba528d 100644
--- a/tests/npbench/polybench/correlation_test.py
+++ b/tests/npbench/polybench/correlation_test.py
@@ -91,7 +91,6 @@ def test_cpu():
     run_correlation(dace.dtypes.DeviceType.CPU)
 
 
-@pytest.mark.skip(reason="Compiler error")
 @pytest.mark.gpu
 def test_gpu():
     run_correlation(dace.dtypes.DeviceType.GPU)
diff --git a/tests/npbench/polybench/deriche_test.py b/tests/npbench/polybench/deriche_test.py
index eace2237af..b2fe7d47e2 100644
--- a/tests/npbench/polybench/deriche_test.py
+++ b/tests/npbench/polybench/deriche_test.py
@@ -160,7 +160,6 @@ def test_cpu():
     run_deriche(dace.dtypes.DeviceType.CPU)
 
 
-@pytest.mark.skip(reason="GPU AutoOpt support")
 @pytest.mark.gpu
 def test_gpu():
     run_deriche(dace.dtypes.DeviceType.GPU)
diff --git a/tests/npbench/polybench/doitgen_test.py b/tests/npbench/polybench/doitgen_test.py
index e114f97e23..06cf3355f5 100644
--- a/tests/npbench/polybench/doitgen_test.py
+++ b/tests/npbench/polybench/doitgen_test.py
@@ -89,7 +89,6 @@ def test_cpu():
     run_doitgen(dace.dtypes.DeviceType.CPU)
 
 
-@pytest.mark.skip(reason="GPU Auto-Opt error")
 @pytest.mark.gpu
 def test_gpu():
     run_doitgen(dace.dtypes.DeviceType.GPU)
diff --git a/tests/npbench/polybench/durbin_test.py b/tests/npbench/polybench/durbin_test.py
index ffb1ed006c..ffeff150d9 100644
--- a/tests/npbench/polybench/durbin_test.py
+++ b/tests/npbench/polybench/durbin_test.py
@@ -98,7 +98,6 @@ def run_durbin(device_type: dace.dtypes.DeviceType):
     return sdfg
 
 
-@pytest.mark.skip(reason="Validation error")
 def test_cpu():
     run_durbin(dace.dtypes.DeviceType.CPU)
 
diff --git a/tests/npbench/polybench/gemver_test.py b/tests/npbench/polybench/gemver_test.py
index 0c8b23222e..58e078fe11 100644
--- a/tests/npbench/polybench/gemver_test.py
+++ b/tests/npbench/polybench/gemver_test.py
@@ -90,7 +90,6 @@ def test_cpu():
     run_gemver(dace.dtypes.DeviceType.CPU)
 
 
-@pytest.mark.skip(reason="Variable not found during codegen")
 @pytest.mark.gpu
 def test_gpu():
     run_gemver(dace.dtypes.DeviceType.GPU)
diff --git a/tests/npbench/polybench/symm_test.py b/tests/npbench/polybench/symm_test.py
index 73b5dca41e..d0bae1edfc 100644
--- a/tests/npbench/polybench/symm_test.py
+++ b/tests/npbench/polybench/symm_test.py
@@ -94,7 +94,6 @@ def test_cpu():
     run_symm(dace.dtypes.DeviceType.CPU)
 
 
-@pytest.mark.skip(reason="Compilation error")
 @pytest.mark.gpu
 def test_gpu():
     run_symm(dace.dtypes.DeviceType.GPU)
diff --git a/tests/npbench/weather_stencils/vadv_test.py b/tests/npbench/weather_stencils/vadv_test.py
index d1ff08fae3..cf01a0cd31 100644
--- a/tests/npbench/weather_stencils/vadv_test.py
+++ b/tests/npbench/weather_stencils/vadv_test.py
@@ -217,13 +217,12 @@ def test_cpu(monkeypatch):
     run_vadv(dace.dtypes.DeviceType.CPU)
 
 
-@pytest.mark.skip(reason="Compiler error")
 @pytest.mark.gpu
 def test_gpu():
     run_vadv(dace.dtypes.DeviceType.GPU)
 
 
-@pytest.mark.skip(reason="Variable not defined")
+@pytest.mark.skip(reason="Xilinx internal compiler error")
 @fpga_test(assert_ii_1=False)
 def test_fpga():
     return run_vadv(dace.dtypes.DeviceType.FPGA)
diff --git a/tests/numpy/linalg_test.py b/tests/numpy/linalg_test.py
index 9211d84130..d7d00a3807 100644
--- a/tests/numpy/linalg_test.py
+++ b/tests/numpy/linalg_test.py
@@ -92,7 +92,7 @@ def tensordot_0(A: dace.float32[3, 3, 3, 3, 3, 3], B: dace.float32[3, 3, 3, 3, 3
 
 # TODO: Enable after fixing cuTENSOR in CI
 #@pytest.mark.gpu
-@pytest.mark.skip
+@pytest.mark.skip('CUTENSOR is not supported in CI')
 def test_tensordot_02():
 
     @dace.program(device=dace.dtypes.DeviceType.GPU)
@@ -131,7 +131,7 @@ def tensordot_1(A: dace.float32[3, 3, 3, 3, 3, 3], B: dace.float32[3, 3, 3, 3, 3
 
 # TODO: Enable after fixing cuTENSOR in CI
 #@pytest.mark.gpu
-@pytest.mark.skip
+@pytest.mark.skip('CUTENSOR is not supported in CI')
 def test_tensordot_12():
 
     @dace.program(device=dace.dtypes.DeviceType.GPU)
@@ -192,7 +192,7 @@ def tensordot_2b(A: dace.float32[3, 3, 3, 3, 3, 3], B: dace.float32[3, 3, 3, 3,
 
 # TODO: Enable after fixing cuTENSOR in CI
 #@pytest.mark.gpu
-@pytest.mark.skip
+@pytest.mark.skip('CUTENSOR is not supported in CI')
 def test_tensordot_22():
 
     @dace.program(device=dace.dtypes.DeviceType.GPU)
diff --git a/tests/numpy/list_globals_test.py b/tests/numpy/list_globals_test.py
index 6281c919a9..8ca9e1eae6 100644
--- a/tests/numpy/list_globals_test.py
+++ b/tests/numpy/list_globals_test.py
@@ -43,7 +43,7 @@ def local_list(A: dace.int32[3, 2, 4]):
     assert np.allclose(result, np.transpose(inp.copy(), axes=local_axes))
 
 
-@pytest.mark.skip
+@pytest.mark.skip('Syntax is not yet supported')
 def test_local_list_with_slice():
     local_axes = [1, 2, 0, 100]
 
diff --git a/tests/numpy/transpose_test.py b/tests/numpy/transpose_test.py
index c56a8a0cda..160728aca6 100644
--- a/tests/numpy/transpose_test.py
+++ b/tests/numpy/transpose_test.py
@@ -50,7 +50,7 @@ def test_transpose():
 
 # TODO: Enable after fixing HPTT in CI
 # @pytest.mark.hptt
-@pytest.mark.skip
+@pytest.mark.skip('HPTT is not supported in CI')
 def test_hptt():
     with dace.config.set_temporary('library', 'ttranspose', 'default_implementation', value='HPTT'):
         test_transpose_axes0()
diff --git a/tests/numpy/ufunc_test.py b/tests/numpy/ufunc_test.py
index b769ab1082..977f2bc47e 100644
--- a/tests/numpy/ufunc_test.py
+++ b/tests/numpy/ufunc_test.py
@@ -56,12 +56,6 @@ def test_ufunc_true_divide_uu(A: dace.uint32[10], B: dace.uint32[10]):
     return np.true_divide(A, B)
 
 
-@pytest.mark.skip
-@compare_numpy_output(non_zero=True, check_dtype=True)
-def test_ufunc_floor_divide_cc(A: dace.complex64[10], B: dace.complex64[10]):
-    return np.floor_divide(A, B)
-
-
 @compare_numpy_output(non_zero=True, check_dtype=True)
 def test_ufunc_floor_divide_ff(A: dace.float32[10], B: dace.float32[10]):
     return np.floor_divide(A, B)
@@ -890,12 +884,6 @@ def test_ufunc_not_equal_ff(A: dace.float32[10], B: dace.float32[10]):
     return np.not_equal(A, B)
 
 
-@pytest.mark.skip
-@compare_numpy_output(check_dtype=True)
-def test_ufunc_logical_and_cc(A: dace.complex64[10], B: dace.complex64[10]):
-    return np.logical_and(A, B)
-
-
 @compare_numpy_output(check_dtype=True)
 def test_ufunc_logical_and_ff(A: dace.float32[10], B: dace.float32[10]):
     return np.logical_and(A, B)
@@ -911,12 +899,6 @@ def test_ufunc_logical_and_su(A: dace.int32[10], B: dace.uint32[10]):
     return np.logical_and(A, B)
 
 
-@pytest.mark.skip
-@compare_numpy_output(check_dtype=True)
-def test_ufunc_logical_or_cc(A: dace.complex64[10], B: dace.complex64[10]):
-    return np.logical_or(A, B)
-
-
 @compare_numpy_output(check_dtype=True)
 def test_ufunc_logical_or_ff(A: dace.float32[10], B: dace.float32[10]):
     return np.logical_or(A, B)
@@ -932,12 +914,6 @@ def test_ufunc_logical_or_su(A: dace.int32[10], B: dace.uint32[10]):
     return np.logical_or(A, B)
 
 
-@pytest.mark.skip
-@compare_numpy_output(check_dtype=True)
-def test_ufunc_logical_xor_cc(A: dace.complex64[10], B: dace.complex64[10]):
-    return np.logical_xor(A, B)
-
-
 @compare_numpy_output(check_dtype=True)
 def test_ufunc_logical_xor_ff(A: dace.float32[10], B: dace.float32[10]):
     return np.logical_xor(A, B)
@@ -998,6 +974,7 @@ def test_ufunc_fmin_nan_ff(A: dace.float32[10], B: dace.float32[10]):
 
 
 def test_ufunc_isfinite_c():
+
     @compare_numpy_output(check_dtype=True)
     def ufunc_isfinite_c(A: dace.complex64[10]):
         A[0] = np.inf
@@ -1016,6 +993,7 @@ def ufunc_isfinite_c(A: dace.complex64[10]):
 
 
 def test_ufunc_isfinite_f():
+
     @compare_numpy_output(check_dtype=True)
     def ufunc_isfinite_f(A: dace.float32[10]):
         A[0] = np.inf
@@ -1036,7 +1014,6 @@ def ufunc_isfinite_f(A: dace.float32[10]):
 # NumPy accepts integer arrays in np.isfinite.
 # However, if any element of an integer array is inf, it will fail because it
 # "<class 'OverflowError'>: cannot convert float infinity to integer"
-@pytest.mark.skip
 @compare_numpy_output(validation_func=lambda a: np.isfinite(a))
 def test_ufunc_isfinite_u(A: dace.uint32[10]):
     A[0] = np.inf
@@ -1045,6 +1022,7 @@ def test_ufunc_isfinite_u(A: dace.uint32[10]):
 
 
 def test_ufunc_isinf_c():
+
     @compare_numpy_output(check_dtype=True)
     def ufunc_isinf_c(A: dace.complex64[10]):
         A[0] = np.inf
@@ -1063,6 +1041,7 @@ def ufunc_isinf_c(A: dace.complex64[10]):
 
 
 def test_ufunc_isinf_f():
+
     @compare_numpy_output(check_dtype=True)
     def ufunc_isinf_f(A: dace.float32[10]):
         A[0] = np.inf
@@ -1083,7 +1062,6 @@ def ufunc_isinf_f(A: dace.float32[10]):
 # NumPy accepts integer arrays in np.isinf.
 # However, if any element of an integer array is inf, it will fail because it
 # "<class 'OverflowError'>: cannot convert float infinity to integer"
-@pytest.mark.skip
 @compare_numpy_output(validation_func=lambda a: np.isinf(a))
 def test_ufunc_isinf_u(A: dace.uint32[10]):
     A[0] = np.inf
@@ -1092,6 +1070,7 @@ def test_ufunc_isinf_u(A: dace.uint32[10]):
 
 
 def test_ufunc_isnan_c():
+
     @compare_numpy_output(check_dtype=True)
     def ufunc_isnan_c(A: dace.complex64[10]):
         A[0] = np.inf
@@ -1110,6 +1089,7 @@ def ufunc_isnan_c(A: dace.complex64[10]):
 
 
 def test_ufunc_isnan_f():
+
     @compare_numpy_output(check_dtype=True)
     def ufunc_isnan_f(A: dace.float32[10]):
         A[0] = np.inf
@@ -1130,7 +1110,6 @@ def ufunc_isnan_f(A: dace.float32[10]):
 # NumPy accepts integer arrays in np.isnan.
 # However, if any element of an integer array is inf, it will fail because it
 # "<class 'OverflowError'>: cannot convert float infinity to integer"
-@pytest.mark.skip
 @compare_numpy_output(validation_func=lambda a: np.isnan(a))
 def test_ufunc_isnan_u(A: dace.uint32[10]):
     A[0] = np.inf
@@ -1320,7 +1299,6 @@ def test_ufunc_clip(A: dace.float32[10]):
     test_ufunc_logaddexp2_ff()
     test_ufunc_true_divide_ff()
     test_ufunc_true_divide_uu()
-    # test_ufunc_floor_divide_cc()
     test_ufunc_floor_divide_ff()
     test_ufunc_floor_divide_uu()
     test_ufunc_floor_divide_ss()
@@ -1486,15 +1464,12 @@ def test_ufunc_clip(A: dace.float32[10]):
     test_ufunc_less_equal_ff()
     test_ufunc_equal_ff()
     test_ufunc_not_equal_ff()
-    # test_ufunc_logical_and_cc()  # TODO: How to convert to bool?
     test_ufunc_logical_and_ff()
     test_ufunc_logical_and_uu()
     test_ufunc_logical_and_su()
-    # test_ufunc_logical_or_cc()   # TODO: How to convert to bool?
     test_ufunc_logical_or_ff()
     test_ufunc_logical_or_uu()
     test_ufunc_logical_or_su()
-    # test_ufunc_logical_xor_cc()  # TODO: How to convert to bool?
     test_ufunc_logical_xor_ff()
     test_ufunc_logical_xor_uu()
     test_ufunc_logical_xor_su()
@@ -1508,13 +1483,13 @@ def test_ufunc_clip(A: dace.float32[10]):
     test_ufunc_fmin_nan_ff()
     test_ufunc_isfinite_c()
     test_ufunc_isfinite_f()
-    # test_ufunc_isfinite_u()
+    test_ufunc_isfinite_u()
     test_ufunc_isinf_c()
     test_ufunc_isinf_f()
-    # test_ufunc_isinf_u())
+    test_ufunc_isinf_u()
     test_ufunc_isnan_c()
     test_ufunc_isnan_f()
-    # test_ufunc_isnan_u()
+    test_ufunc_isnan_u()
     test_ufunc_signbit_c()
     test_ufunc_signbit_f()
     test_ufunc_signbit_u()
diff --git a/tests/python_frontend/assignment_statements_test.py b/tests/python_frontend/assignment_statements_test.py
index 0681c79c49..f8538aa848 100644
--- a/tests/python_frontend/assignment_statements_test.py
+++ b/tests/python_frontend/assignment_statements_test.py
@@ -72,7 +72,7 @@ def starred_target(a: dace.float32[1]):
     return b, c, d, e
 
 
-@pytest.mark.skip
+@pytest.mark.skip('Syntax is not yet supported')
 def test_starred_target():
     a = np.zeros((1, ), dtype=np.float32)
     a[0] = np.pi
@@ -94,7 +94,7 @@ def attribute_reference(a: mystruct[1]):
     a.b[0] = 6
 
 
-@pytest.mark.skip
+@pytest.mark.skip('Syntax is not yet supported')
 def test_attribute_reference():
     a = np.ndarray((1, ), dtype=np.dtype(mystruct.as_ctypes()))
     attribute_reference(a=a)
diff --git a/tests/python_frontend/augassign_wcr_test.py b/tests/python_frontend/augassign_wcr_test.py
index e6964261fe..46c0dd8802 100644
--- a/tests/python_frontend/augassign_wcr_test.py
+++ b/tests/python_frontend/augassign_wcr_test.py
@@ -44,11 +44,11 @@ def augassign_wcr3(A: dace.int32[10, 10, 10], B: dace.int32[10], W: dace.bool_[1
 
 @dace.program
 def augassign_wcr4():
-    a = np.zeros((10,))
+    a = np.zeros((10, ))
     for i in dace.map[1:9]:
-        a[i-1] += 1
+        a[i - 1] += 1
         a[i] += 2
-        a[i+1] += 3
+        a[i + 1] += 3
     return a
 
 
@@ -121,6 +121,7 @@ def test_augassign_wcr3():
 
 
 def test_augassign_no_wcr():
+
     @dace.program
     def no_wcr(A: dace.int32[5, 5, 5]):
         A[2, 3, :] += A[3, 2, :]
@@ -139,6 +140,7 @@ def no_wcr(A: dace.int32[5, 5, 5]):
 
 
 def test_augassign_no_wcr2():
+
     @dace.program
     def no_wcr(A: dace.int32[5, 5, 5]):
         A[2, 3, 1:4] += A[2:5, 1, 4]
@@ -156,9 +158,8 @@ def no_wcr(A: dace.int32[5, 5, 5]):
     assert (np.allclose(A, ref))
 
 
-@pytest.mark.skip
 def test_augassign_wcr4():
-    
+
     with dace.config.set_temporary('frontend', 'avoid_wcr', value=False):
         val = augassign_wcr4()
         ref = augassign_wcr4.f()
diff --git a/tests/python_frontend/callback_autodetect_test.py b/tests/python_frontend/callback_autodetect_test.py
index fe567f18ad..6f34dee2b1 100644
--- a/tests/python_frontend/callback_autodetect_test.py
+++ b/tests/python_frontend/callback_autodetect_test.py
@@ -163,7 +163,7 @@ def tasklet_callback(A: dace.float64[N, N], B: dace.float64[N, N]):
             b = sq(a)
 
 
-@pytest.mark.skip
+@pytest.mark.skip('Syntax is not yet supported')
 def test_callback_tasklet():
     A = np.random.rand(24, 24)
     B = np.random.rand(24, 24)
@@ -319,7 +319,7 @@ def same_name_nested():
 
 
 # Cannot run test without cupy
-@pytest.mark.skip
+@pytest.mark.gpu
 def test_gpu_callback():
     import cupy as cp
 
@@ -906,7 +906,7 @@ def tester(a: dace.float64[20]):
     assert np.allclose(aa, expected)
 
 
-@pytest.mark.skip
+@pytest.mark.skip('Test requires GUI')
 def test_matplotlib_with_compute():
     """
     Stacked bar plot example from Matplotlib using callbacks and pyobjects.
@@ -951,7 +951,7 @@ def tester():
     test_reorder()
     test_reorder_nested()
     test_callback_samename()
-    # test_gpu_callback()
+    test_gpu_callback()
     test_bad_closure()
     test_object_with_nested_callback()
     test_two_parameters_same_name()
diff --git a/tests/python_frontend/conditional_assignment_test.py b/tests/python_frontend/conditional_assignment_test.py
index d138ad88c5..7726b3a3e1 100644
--- a/tests/python_frontend/conditional_assignment_test.py
+++ b/tests/python_frontend/conditional_assignment_test.py
@@ -76,7 +76,7 @@ def some_func(field, may_be_none):
     assert np.allclose(field, 1.0)
 
 
-@pytest.mark.skip
+@pytest.mark.skip('Reference scalars unsupported in Python frontend (fails without simplification)')
 def test_maybe_none_scalar_arg():
     @dace.program
     def some_func(field, a_scalar):
diff --git a/tests/python_frontend/lambda_test.py b/tests/python_frontend/lambda_test.py
index b2d75a5e16..be3fe58579 100644
--- a/tests/python_frontend/lambda_test.py
+++ b/tests/python_frontend/lambda_test.py
@@ -23,7 +23,7 @@ def lamb(A: dace.float64[20], B: dace.float64[20], C: dace.float64[20]):
     assert np.allclose(A, B + C)
 
 
-@pytest.mark.skip
+@pytest.mark.skip('Syntax is not yet supported')
 def test_inline_lambda_scalar():
     @dace.program
     def lamb(A: dace.float64[20], B: dace.float64[20], C: dace.float64[20]):
@@ -38,7 +38,7 @@ def lamb(A: dace.float64[20], B: dace.float64[20], C: dace.float64[20]):
     assert np.allclose(A, B + C)
 
 
-@pytest.mark.skip
+@pytest.mark.skip('Syntax is not yet supported')
 def test_inline_lambda_array():
     @dace.program
     def lamb(A: dace.float64[20], B: dace.float64[20], C: dace.float64[20]):
@@ -52,7 +52,7 @@ def lamb(A: dace.float64[20], B: dace.float64[20], C: dace.float64[20]):
     assert np.allclose(A, B + C)
 
 
-@pytest.mark.skip
+@pytest.mark.skip('Syntax is not yet supported')
 def test_lambda_global():
     f = lambda a, b: a + b
 
@@ -67,7 +67,7 @@ def lamb(A: dace.float64[20], B: dace.float64[20], C: dace.float64[20]):
     assert np.allclose(A, B + C)
 
 
-@pytest.mark.skip
+@pytest.mark.skip('Syntax is not yet supported')
 def test_lambda_call_jit():
     @dace.program
     def lamb(A, B, C, f):
@@ -81,7 +81,7 @@ def lamb(A, B, C, f):
     assert np.allclose(A, B + C)
 
 
-@pytest.mark.skip
+@pytest.mark.skip('Syntax is not yet supported')
 def test_lambda_nested_call():
     @dace.program
     def lamb2(A, B, C, f):
diff --git a/tests/python_frontend/string_test.py b/tests/python_frontend/string_test.py
index a22ef1dd18..533057b092 100644
--- a/tests/python_frontend/string_test.py
+++ b/tests/python_frontend/string_test.py
@@ -75,7 +75,7 @@ def tester():
     assert np.allclose(tester(), False)
 
 
-@pytest.mark.skip
+@pytest.mark.skip('Syntax is not yet supported')
 def test_string_literal():
 
     @dace
@@ -85,7 +85,7 @@ def tester():
     assert tester()[0] == 'Hello World!'
 
 
-@pytest.mark.skip
+@pytest.mark.skip('Syntax is not yet supported')
 def test_bytes_literal():
 
     @dace
diff --git a/tests/python_frontend/structures/structure_python_test.py b/tests/python_frontend/structures/structure_python_test.py
index 8190e776b9..bc4ab58d7c 100644
--- a/tests/python_frontend/structures/structure_python_test.py
+++ b/tests/python_frontend/structures/structure_python_test.py
@@ -182,7 +182,7 @@ def rgf_leftToRight(A: BlockTriDiagonal, B: BlockTriDiagonal, n_: dace.int32, nb
     assert np.allclose(B.lower, B_lower)
 
 
-@pytest.mark.skip
+@pytest.mark.skip('Compiler error (const conversion)')
 @pytest.mark.gpu
 def test_read_structure_gpu():
 
diff --git a/tests/reduce_strided_disabledtest.py b/tests/reduce_strided_disabledtest.py
index 72d9c821ca..6a6f1a24e0 100644
--- a/tests/reduce_strided_disabledtest.py
+++ b/tests/reduce_strided_disabledtest.py
@@ -5,31 +5,29 @@
 import numpy as np
 import pytest
 
-# Python version of the SDFG below
-# @dace.program
-# def reduce_with_strides(A: dace.float64[50, 50], B: dace.float64[25]):
-#     B[:] = dace.reduce(lambda a,b: a+b, A[::2, ::2], axis=0,
-#                        identity=0)
 
-reduce_with_strides = dace.SDFG('reduce_with_strides')
-reduce_with_strides.add_array('A', [50, 50], dace.float64)
-reduce_with_strides.add_array('B', [25], dace.float64)
-
-state = reduce_with_strides.add_state()
-node_a = state.add_read('A')
-node_b = state.add_write('B')
-red = state.add_reduce('lambda a,b: a+b', [0], 0)
-state.add_nedge(node_a, red, dace.Memlet.simple('A', '0:50:2, 0:50:2'))
-state.add_nedge(red, node_b, dace.Memlet.simple('B', '0:25'))
-
-
-@pytest.mark.skip
+@pytest.mark.skip('Incorrect outputs')
 def test_strided_reduce():
     A = np.random.rand(50, 50)
     B = np.random.rand(25)
 
-    sdfg = copy.deepcopy(reduce_with_strides)
-    sdfg(A=A, B=B)
+    # Python version of the SDFG below
+    # @dace.program
+    # def reduce_with_strides(A: dace.float64[50, 50], B: dace.float64[25]):
+    #     B[:] = dace.reduce(lambda a,b: a+b, A[::2, ::2], axis=0,
+    #                        identity=0)
+
+    reduce_with_strides = dace.SDFG('reduce_with_strides')
+    reduce_with_strides.add_array('A', [50, 50], dace.float64)
+    reduce_with_strides.add_array('B', [25], dace.float64)
+
+    state = reduce_with_strides.add_state()
+    node_a = state.add_read('A')
+    node_b = state.add_write('B')
+    red = state.add_reduce('lambda a,b: a+b', [0], 0)
+    state.add_nedge(node_a, red, dace.Memlet.simple('A', '0:50:2, 0:50:2'))
+    state.add_nedge(red, node_b, dace.Memlet.simple('B', '0:25'))
+    reduce_with_strides(A=A, B=B)
 
     assert np.allclose(B, np.sum(A[::2, ::2], axis=0))
 
diff --git a/tests/rtl/hardware_test.py b/tests/rtl/hardware_test.py
index b6c01fab93..b17da2050f 100644
--- a/tests/rtl/hardware_test.py
+++ b/tests/rtl/hardware_test.py
@@ -372,8 +372,7 @@ def test_hardware_add42_single():
     return sdfg
 
 
-@pytest.mark.skip(reason="This test is covered by the Xilinx tests.")
-def test_hardware_axpy_double_pump(veclen=2):
+def _hardware_axpy_double_pump(veclen=2):
     '''
     Tests manual application of the multi-pumping optimization applied to the AXPY program from BLAS.
 
@@ -415,7 +414,7 @@ def test_hardware_axpy_double_pump_vec2():
     '''
     Tests double pumping with a vector length of 2.
     '''
-    return test_hardware_axpy_double_pump(veclen=2)
+    return _hardware_axpy_double_pump(veclen=2)
 
 
 @rtl_test()
@@ -423,7 +422,7 @@ def test_hardware_axpy_double_pump_vec4():
     '''
     Tests double pumping with a vector length of 4.
     '''
-    return test_hardware_axpy_double_pump(veclen=4)
+    return _hardware_axpy_double_pump(veclen=4)
 
 
 @rtl_test()
@@ -493,7 +492,7 @@ def np_vadd(x: dace.float32[N], y: dace.float32[N]):
         return sdfg
 
 
-# TODO disabled due to problem with array of streams in Vitis 2021.1
+# Disabled due to problem with array of streams in Vitis 2021.1
 #rtl_test()
 #def test_hardware_add42_multi():
 #    N = dace.symbol('N')
@@ -522,7 +521,6 @@ def np_vadd(x: dace.float32[N], y: dace.float32[N]):
         test_hardware_vadd(None)
         test_hardware_vadd_temporal_vectorization(None)
         test_hardware_add42_single(None)
-        # TODO disabled due to problem with array of streams in Vitis 2021.1
         #test_hardware_add42_multi(None)
         test_hardware_axpy_double_pump_vec2(None)
         test_hardware_axpy_double_pump_vec4(None)
diff --git a/tests/sdfg/scalar_return.py b/tests/sdfg/scalar_return.py
index 82bdb48c6b..1949afab16 100644
--- a/tests/sdfg/scalar_return.py
+++ b/tests/sdfg/scalar_return.py
@@ -62,7 +62,7 @@ def tuple_retval_sdfg() -> dace.SDFG:
     return sdfg
 
 
-@pytest.mark.skip("Scalar return is not implement.")
+@pytest.mark.skip("Scalar return is not implemented")
 def test_scalar_return():
 
     sdfg = single_retval_sdfg()
@@ -75,7 +75,7 @@ def test_scalar_return():
     assert A[3] == res
 
 
-@pytest.mark.skip("Scalar return is not implement.")
+@pytest.mark.skip("Scalar return is not implemented")
 def test_scalar_return_tuple():
 
     sdfg = tuple_retval_sdfg()
diff --git a/tests/symbol_dependent_transients_test.py b/tests/symbol_dependent_transients_test.py
index 2c7ca94c6f..f67b0dc416 100644
--- a/tests/symbol_dependent_transients_test.py
+++ b/tests/symbol_dependent_transients_test.py
@@ -154,7 +154,7 @@ def test_symbol_dependent_pinned_array():
     assert (np.allclose(B, B_ref))
 
 
-@pytest.mark.skip  # @pytest.mark.gpu
+@pytest.mark.skip('Invalid address accessed in kernel')  # @pytest.mark.gpu
 def test_symbol_dependent_gpu_view():
     # NOTE: This test cannot produce the correct result since the input
     # data of the reduction are not contiguous and cub:reduce doesn't support
@@ -173,7 +173,7 @@ def test_symbol_dependent_gpu_view():
     assert (np.allclose(B, B_ref))
 
 
-@pytest.mark.skip
+@pytest.mark.skip('FPGA compiler error')
 def test_symbol_dependent_fpga_global_array():
     A = np.random.randn(10, 10, 10)
     B = np.ndarray(10, dtype=np.float64)

From c146ba20eeb6935234c67a503b0a21d8a39043a2 Mon Sep 17 00:00:00 2001
From: Tal Ben-Nun <tbennun@users.noreply.github.com>
Date: Mon, 11 Nov 2024 06:10:04 -0800
Subject: [PATCH 27/33] Fix OpenMP dynamic loop bounds that use persistent
 memory (#1746)

Fixes #1550
---
 dace/codegen/targets/cpu.py               |  2 +-
 tests/codegen/allocation_lifetime_test.py | 40 ++++++++++++++++++++---
 2 files changed, 37 insertions(+), 5 deletions(-)

diff --git a/dace/codegen/targets/cpu.py b/dace/codegen/targets/cpu.py
index 160855458d..9ba202757e 100644
--- a/dace/codegen/targets/cpu.py
+++ b/dace/codegen/targets/cpu.py
@@ -1845,7 +1845,7 @@ def _generate_MapEntry(
 
         # Define all input connectors of this map entry
         for e in dynamic_map_inputs(state_dfg, node):
-            if e.data.data != e.dst_conn:
+            if cpp.ptr(e.data.data, sdfg.arrays[e.data.data], sdfg, self._frame) != e.dst_conn:
                 callsite_stream.write(
                     self.memlet_definition(sdfg, e.data, False, e.dst_conn, e.dst.in_connectors[e.dst_conn]), cfg,
                     state_id, node)
diff --git a/tests/codegen/allocation_lifetime_test.py b/tests/codegen/allocation_lifetime_test.py
index 380367057a..2b53e87644 100644
--- a/tests/codegen/allocation_lifetime_test.py
+++ b/tests/codegen/allocation_lifetime_test.py
@@ -398,6 +398,31 @@ def perscal(a: dace.float64[20]):
     assert np.allclose(a[3], 5)
 
 
+def test_persistent_loop_bound():
+    """
+    Code originates from Issue #1550.
+    Tests both ``for`` and OpenMP parallel ``for`` loop bounds with persistent storage.
+    """
+    N = dace.symbol('N')
+
+    @dace.program(auto_optimize=True)
+    def tester(L: dace.float64[N, N], index: dace.uint64, active_size: dace.uint64):
+        for i in range(index, active_size - 1):
+            L[i + 1][i] = 1.0
+
+            for j in range(i, dace.int64(active_size - 1)):
+                L[j + 1][i] = 2.0
+
+    l = np.random.rand(10, 10)
+    index = 2
+    active_size = 7
+    l_ref = np.copy(l)
+    tester.f(l_ref, index, active_size)
+    tester(l, index, active_size)
+
+    assert np.allclose(l, l_ref)
+
+
 def test_double_nested_persistent_write():
     sdfg = dace.SDFG('npw_inner')
     sdfg.add_array('pers', [20], dace.float64)
@@ -451,10 +476,16 @@ def test_branched_allocation(mode):
     sdfg.add_edge(state_br1_1, state_merge, dace.InterstateEdge())
     sdfg.add_edge(state_br2_1, state_merge, dace.InterstateEdge())
 
-    tasklet1 = state_br1.add_tasklet(name="br1", inputs=[], outputs=["out"], \
-            code="out = 1;", language=dace.Language.CPP)
-    tasklet2 = state_br2.add_tasklet(name="br2", inputs=[], outputs=["out"], \
-            code="out = 1;", language=dace.Language.CPP)
+    tasklet1 = state_br1.add_tasklet(name="br1",
+                                     inputs=[],
+                                     outputs=["out"],
+                                     code="out = 1;",
+                                     language=dace.Language.CPP)
+    tasklet2 = state_br2.add_tasklet(name="br2",
+                                     inputs=[],
+                                     outputs=["out"],
+                                     code="out = 1;",
+                                     language=dace.Language.CPP)
 
     arr_A = state_br1.add_write("A")
     memlet = dace.Memlet(expr="A[1]")
@@ -576,6 +607,7 @@ def test_multisize():
     test_persistent_scalar()
     test_persistent_scalar_in_map()
     test_persistent_array_access()
+    test_persistent_loop_bound()
     test_double_nested_persistent_write()
     test_branched_allocation('global')
     test_branched_allocation('singlevalue')

From 02c9c3787d0c16c5a7a8ba006bf446d24c9a0443 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Philip=20M=C3=BCller?=
 <147368808+philip-paul-mueller@users.noreply.github.com>
Date: Mon, 11 Nov 2024 20:08:08 +0100
Subject: [PATCH 28/33] Fixing `SDFGState._read_and_write_sets()` (#1747)

Removed some asserts that were to strict from
`SDFGState._read_and_write_sets()`.

If a subset is `None` the function assumes that corresponding array is
fully accessed.
Before, there was an `assert` that ensured that this assumption is true.
However, the implementation also assumed that this could be verified,
either because the same symbols were used or the size was known.

But this if not necessarily the case, if the two involved arrays uses
different symbols, that however, are always the same.
The other reason was that before the size was estimated using
`total_size`, which has a well defined meaning for an `Array` but in
case of a `View` its meaning is not fully clear.

For these reasons the asserts was removed.

---------

Co-authored-by: Tal Ben-Nun <tbennun@users.noreply.github.com>
---
 dace/sdfg/state.py                      | 26 ++++++--------
 tests/npbench/misc/stockham_fft_test.py |  2 +-
 tests/sdfg/state_test.py                | 47 +++++++++++++++++++++++++
 3 files changed, 59 insertions(+), 16 deletions(-)

diff --git a/dace/sdfg/state.py b/dace/sdfg/state.py
index b982dfd718..c99f45bb44 100644
--- a/dace/sdfg/state.py
+++ b/dace/sdfg/state.py
@@ -786,26 +786,22 @@ def _read_and_write_sets(self) -> Tuple[Dict[AnyStr, List[Subset]], Dict[AnyStr,
                 # NOTE: In certain cases the corresponding subset might be None, in this case
                 #   we assume that the whole array is written, which is the default behaviour.
                 ac_desc = n.desc(self.sdfg)
-                ac_size = ac_desc.total_size
-                in_subsets = dict()
-                for in_edge in in_edges:
-                    # Ensure that if the destination subset is not given, our assumption, that the
-                    #  whole array is written to, is valid, by testing if the memlet transfers the
-                    #  whole array.
-                    assert (in_edge.data.dst_subset is not None) or (in_edge.data.num_elements() == ac_size)
-                    in_subsets[in_edge] = (
-                            sbs.Range.from_array(ac_desc)
-                            if in_edge.data.dst_subset is None
-                            else in_edge.data.dst_subset
+                in_subsets = {
+                    in_edge: (
+                        sbs.Range.from_array(ac_desc)
+                        if in_edge.data.dst_subset is None
+                        else in_edge.data.dst_subset
                     )
-                out_subsets = dict()
-                for out_edge in out_edges:
-                    assert (out_edge.data.src_subset is not None) or (out_edge.data.num_elements() == ac_size)
-                    out_subsets[out_edge] = (
+                    for in_edge in in_edges
+                }
+                out_subsets = {
+                    out_edge: (
                         sbs.Range.from_array(ac_desc)
                         if out_edge.data.src_subset is None
                         else out_edge.data.src_subset
                     )
+                    for out_edge in out_edges
+                }
 
                 # Update the read and write sets of the subgraph.
                 if in_edges:
diff --git a/tests/npbench/misc/stockham_fft_test.py b/tests/npbench/misc/stockham_fft_test.py
index 8fc5e88203..5878cf621a 100644
--- a/tests/npbench/misc/stockham_fft_test.py
+++ b/tests/npbench/misc/stockham_fft_test.py
@@ -185,4 +185,4 @@ def test_fpga():
     elif target == "gpu":
         run_stockham_fft(dace.dtypes.DeviceType.GPU)
     elif target == "fpga":
-        run_stockham_fft(dace.dtypes.DeviceType.FPGA)
\ No newline at end of file
+        run_stockham_fft(dace.dtypes.DeviceType.FPGA)
diff --git a/tests/sdfg/state_test.py b/tests/sdfg/state_test.py
index 4bde3788e0..dc8ede776f 100644
--- a/tests/sdfg/state_test.py
+++ b/tests/sdfg/state_test.py
@@ -145,6 +145,52 @@ def test_read_and_write_set_selection():
                 assert found_match, f"Could not find the subset '{exp}' only got '{computed_sets}'"
 
 
+def test_read_and_write_set_names():
+    sdfg = dace.SDFG('test_read_and_write_set_names')
+    state = sdfg.add_state(is_start_block=True)
+
+    # The arrays use different symbols for their sizes, but they are known to be the
+    #  same. This happens for example if the SDFG is the result of some automatic
+    #  translation from another IR, such as GTIR in GT4Py.
+    names = ["A", "B"]
+    for name in names:
+        sdfg.add_symbol(f"{name}_size_0", dace.int32)
+        sdfg.add_symbol(f"{name}_size_1", dace.int32)
+        sdfg.add_array(
+                name,
+                shape=(f"{name}_size_0", f"{name}_size_1"),
+                dtype=dace.float64,
+                transient=False,
+        )
+    A, B = (state.add_access(name) for name in names)
+
+    # Print copy `A` into `B`.
+    #  Because, `dst_subset` is `None` we expect that everything is transferred.
+    state.add_nedge(
+            A,
+            B,
+            dace.Memlet("A[0:A_size_0, 0:A_size_1]"),
+    )
+    expected_read_set = {
+            "A": [sbs.Range.from_string("0:A_size_0, 0:A_size_1")],
+    }
+    expected_write_set = {
+            "B": [sbs.Range.from_string("0:B_size_0, 0:B_size_1")],
+    }
+    read_set, write_set = state._read_and_write_sets()
+
+    for expected_sets, computed_sets in [(expected_read_set, read_set), (expected_write_set, write_set)]:
+        assert expected_sets.keys() == computed_sets.keys(), f"Expected the set to contain '{expected_sets.keys()}' but got '{computed_sets.keys()}'."
+        for access_data in expected_sets.keys():
+            for exp in expected_sets[access_data]:
+                found_match = False
+                for res in computed_sets[access_data]:
+                    if res == exp:
+                        found_match = True
+                        break
+                assert found_match, f"Could not find the subset '{exp}' only got '{computed_sets}'"
+
+
 def test_add_mapped_tasklet():
     sdfg = dace.SDFG("test_add_mapped_tasklet")
     state = sdfg.add_state(is_start_block=True)
@@ -173,5 +219,6 @@ def test_add_mapped_tasklet():
     test_read_and_write_set_filter()
     test_read_write_set()
     test_read_write_set_y_formation()
+    test_read_and_write_set_names()
     test_deepcopy_state()
     test_add_mapped_tasklet()

From 17e4a888882a366930e9d00df626bded20c3d49a Mon Sep 17 00:00:00 2001
From: Tal Ben-Nun <tbennun@users.noreply.github.com>
Date: Wed, 13 Nov 2024 04:35:04 -0800
Subject: [PATCH 29/33] Fix temporary transient counter during Python parsing
 of nested calls (#1745)

Fixes #1139
---
 dace/frontend/python/newast.py                |  3 +
 dace/sdfg/sdfg.py                             | 14 ++++
 tests/npbench/misc/mandelbrot1_test.py        |  2 +-
 tests/npbench/misc/mandelbrot2_test.py        |  2 +-
 .../nested_name_accesses_test.py              | 70 +++++++++++++++----
 5 files changed, 76 insertions(+), 15 deletions(-)

diff --git a/dace/frontend/python/newast.py b/dace/frontend/python/newast.py
index b4e83cc1e7..1cbb8e67c9 100644
--- a/dace/frontend/python/newast.py
+++ b/dace/frontend/python/newast.py
@@ -3940,6 +3940,9 @@ def _parse_sdfg_call(self, funcname: str, func: Union[SDFG, SDFGConvertible], no
         for arg in args_to_remove:
             args.remove(arg)
 
+        # Refresh temporary transient counter of the nested SDFG
+        sdfg.refresh_temp_transients()
+
         # Change connector names
         updated_args = []
         arrays_before = list(sdfg.arrays.items())
diff --git a/dace/sdfg/sdfg.py b/dace/sdfg/sdfg.py
index 1b449403d5..927f033584 100644
--- a/dace/sdfg/sdfg.py
+++ b/dace/sdfg/sdfg.py
@@ -1952,6 +1952,20 @@ def temp_data_name(self):
         self._temp_transients += 1
         return name
 
+    def refresh_temp_transients(self):
+        """
+        Updates the temporary transient counter of this SDFG by querying the maximum number among the
+        ``__tmp###`` data descriptors.
+        """
+        temp_transients = [k[5:] for k in self.arrays.keys() if k.startswith('__tmp')]
+        max_temp_transient = 0
+        for arr_suffix in temp_transients:
+            try:
+                max_temp_transient = max(max_temp_transient, int(arr_suffix))
+            except ValueError:  # Not of the form __tmp###
+                continue
+        self._temp_transients = max_temp_transient + 1
+
     def add_temp_transient(self,
                            shape,
                            dtype,
diff --git a/tests/npbench/misc/mandelbrot1_test.py b/tests/npbench/misc/mandelbrot1_test.py
index 521d41c560..6fb8262aa2 100644
--- a/tests/npbench/misc/mandelbrot1_test.py
+++ b/tests/npbench/misc/mandelbrot1_test.py
@@ -97,7 +97,7 @@ def run_mandelbrot1(device_type: dace.dtypes.DeviceType):
         Z, N = sdfg(xmin, xmax, ymin, ymax, maxiter, horizon)
 
     # Compute ground truth and validate
-    Z_ref, N_ref = ground_truth(xmin, xmax, ymin, ymax, xn, yn, maxiter)
+    Z_ref, N_ref = ground_truth(xmin, xmax, ymin, ymax, XN, YN, maxiter)
     assert np.allclose(Z, Z_ref)
     assert np.allclose(N, N_ref)
     return sdfg
diff --git a/tests/npbench/misc/mandelbrot2_test.py b/tests/npbench/misc/mandelbrot2_test.py
index aaca2c6db9..1be84d0c1c 100644
--- a/tests/npbench/misc/mandelbrot2_test.py
+++ b/tests/npbench/misc/mandelbrot2_test.py
@@ -145,7 +145,7 @@ def run_mandelbrot2(device_type: dace.dtypes.DeviceType):
         Z, N = sdfg(xmin, xmax, ymin, ymax, maxiter, horizon)
 
     # Compute ground truth and validate
-    Z_ref, N_ref = ground_truth(xmin, xmax, ymin, ymax, xn, yn, maxiter)
+    Z_ref, N_ref = ground_truth(xmin, xmax, ymin, ymax, XN, YN, maxiter)
     assert np.allclose(Z, Z_ref)
     assert np.allclose(N, N_ref)
     return sdfg
diff --git a/tests/python_frontend/nested_name_accesses_test.py b/tests/python_frontend/nested_name_accesses_test.py
index 1e5b18b840..424f280771 100644
--- a/tests/python_frontend/nested_name_accesses_test.py
+++ b/tests/python_frontend/nested_name_accesses_test.py
@@ -1,4 +1,4 @@
-# Copyright 2019-2021 ETH Zurich and the DaCe authors. All rights reserved.
+# Copyright 2019-2024 ETH Zurich and the DaCe authors. All rights reserved.
 import dace as dc
 import numpy as np
 import os
@@ -30,6 +30,7 @@ def test_nested_name_accesses():
 
 
 def test_nested_offset_access():
+
     @dc.program
     def nested_offset_access(inp: dc.float64[6, 5, 5]):
         out = np.zeros((5, 5, 5), np.float64)
@@ -46,6 +47,7 @@ def nested_offset_access(inp: dc.float64[6, 5, 5]):
 
 
 def test_nested_offset_access_dappy():
+
     @dc.program
     def nested_offset_access(inp: dc.float64[6, 5, 5]):
         out = np.zeros((5, 5, 5), np.float64)
@@ -66,6 +68,7 @@ def nested_offset_access(inp: dc.float64[6, 5, 5]):
 
 
 def test_nested_multi_offset_access():
+
     @dc.program
     def nested_offset_access(inp: dc.float64[6, 5, 10]):
         out = np.zeros((5, 5, 10), np.float64)
@@ -83,6 +86,7 @@ def nested_offset_access(inp: dc.float64[6, 5, 10]):
 
 
 def test_nested_multi_offset_access_dappy():
+
     @dc.program
     def nested_offset_access(inp: dc.float64[6, 5, 10]):
         out = np.zeros((5, 5, 10), np.float64)
@@ -104,6 +108,7 @@ def nested_offset_access(inp: dc.float64[6, 5, 10]):
 
 
 def test_nested_dec_offset_access():
+
     @dc.program
     def nested_offset_access(inp: dc.float64[6, 5, 5]):
         out = np.zeros((5, 5, 5), np.float64)
@@ -120,6 +125,7 @@ def nested_offset_access(inp: dc.float64[6, 5, 5]):
 
 
 def test_nested_dec_offset_access_dappy():
+
     @dc.program
     def nested_offset_access(inp: dc.float64[6, 5, 5]):
         out = np.zeros((5, 5, 5), np.float64)
@@ -140,6 +146,7 @@ def nested_offset_access(inp: dc.float64[6, 5, 5]):
 
 
 def test_nested_offset_access_nested_dependency():
+
     @dc.program
     def nested_offset_access_nested_dep(inp: dc.float64[6, 5, 5]):
         out = np.zeros((5, 5, 5), np.float64)
@@ -161,6 +168,7 @@ def nested_offset_access_nested_dep(inp: dc.float64[6, 5, 5]):
 
 
 def test_nested_offset_access_nested_dependency_dappy():
+
     @dc.program
     def nested_offset_access_nested_dep(inp: dc.float64[6, 5, 10]):
         out = np.zeros((5, 5, 10), np.float64)
@@ -188,19 +196,19 @@ def test_access_to_nested_transient():
     NBLOCKS = 5
 
     @dc.program
-    def small_wip(inp: dc.float64[KLEV+1, KLON, NBLOCKS], out: dc.float64[KLEV, KLON, NBLOCKS]):
+    def small_wip(inp: dc.float64[KLEV + 1, KLON, NBLOCKS], out: dc.float64[KLEV, KLON, NBLOCKS]):
         for jn in dc.map[0:NBLOCKS]:
-            tmp = np.zeros([KLEV+1, KLON])
+            tmp = np.zeros([KLEV + 1, KLON])
             for jl in range(KLON):
                 for jk in range(KLEV):
-                    tmp[jk, jl] = inp[jk, jl, jn] + inp[jk+1, jl, jn]
+                    tmp[jk, jl] = inp[jk, jl, jn] + inp[jk + 1, jl, jn]
 
             for jl in range(KLON):
                 for jk in range(KLEV):
-                    out[jk, jl, jn] = tmp[jk, jl] + tmp[jk+1, jl]
-    
+                    out[jk, jl, jn] = tmp[jk, jl] + tmp[jk + 1, jl]
+
     rng = np.random.default_rng(42)
-    inp = rng.random((KLEV+1, KLON, NBLOCKS))
+    inp = rng.random((KLEV + 1, KLON, NBLOCKS))
     ref = np.zeros((KLEV, KLON, NBLOCKS))
     val = np.zeros((KLEV, KLON, NBLOCKS))
 
@@ -217,14 +225,14 @@ def test_access_to_nested_transient_dappy():
     NBLOCKS = 5
 
     @dc.program
-    def small_wip_dappy(inp: dc.float64[KLEV+1, KLON, NBLOCKS], out: dc.float64[KLEV, KLON, NBLOCKS]):
+    def small_wip_dappy(inp: dc.float64[KLEV + 1, KLON, NBLOCKS], out: dc.float64[KLEV, KLON, NBLOCKS]):
         for jn in dc.map[0:NBLOCKS]:
-            tmp = np.zeros([KLEV+1, KLON])
+            tmp = np.zeros([KLEV + 1, KLON])
             for jl in range(KLON):
                 for jk in range(KLEV):
                     with dc.tasklet():
                         in1 << inp[jk, jl, jn]
-                        in2 << inp[jk+1, jl, jn]
+                        in2 << inp[jk + 1, jl, jn]
                         out1 >> tmp[jk, jl]
                         out1 = in1 + in2
 
@@ -232,12 +240,12 @@ def small_wip_dappy(inp: dc.float64[KLEV+1, KLON, NBLOCKS], out: dc.float64[KLEV
                 for jk in range(KLEV):
                     with dc.tasklet():
                         in1 << tmp[jk, jl]
-                        in2 << tmp[jk+1, jl]
+                        in2 << tmp[jk + 1, jl]
                         out1 >> out[jk, jl, jn]
                         out1 = in1 + in2
-    
+
     rng = np.random.default_rng(42)
-    inp = rng.random((KLEV+1, KLON, NBLOCKS))
+    inp = rng.random((KLEV + 1, KLON, NBLOCKS))
     ref = np.zeros((KLEV, KLON, NBLOCKS))
     val = np.zeros((KLEV, KLON, NBLOCKS))
 
@@ -247,6 +255,41 @@ def small_wip_dappy(inp: dc.float64[KLEV+1, KLON, NBLOCKS], out: dc.float64[KLEV
     assert np.allclose(val, ref)
 
 
+def test_issue_1139():
+    """
+    Regression test generated from issue #1139.
+
+    The origin of the bug was in the Python frontend: An SDFG parsed by the frontend kept
+    a number called ``_temp_transients`` that specifies how many ``__tmp*`` arrays have been created.
+    This number is used to avoid name clashes when inlining SDFGs (although unnecessary).
+    However, if a nested SDFG had already been simplified, where transformations may change the number
+    of transients (or add new ones via inlining, which is happening in this bug), the ``_temp_transients``
+    field becomes out of date and renaming the fields during inlining removes data descriptors.
+    """
+    XN = dc.symbol('XN')
+    YN = dc.symbol('YN')
+    N = dc.symbol('N')
+
+    @dc.program
+    def nester(start: dc.float64, stop: dc.float64, X: dc.float64[N]):
+        dist = (stop - start) / (N - 1)
+        for i in dc.map[0:N]:
+            X[i] = start + i * dist
+
+    @dc.program
+    def tester(xmin: dc.float64, xmax: dc.float64):
+        a = np.ndarray((XN, YN), dtype=np.int64)
+        b = np.ndarray((XN, YN), dtype=np.int64)
+        c = np.ndarray((XN, ), dtype=np.float64)
+        nester(xmin, xmax, c)
+        return c
+
+    xmin = 0.123
+    xmax = 4.567
+    c = tester(xmin, xmax, XN=30, YN=40)
+    assert np.allclose(c, np.linspace(xmin, xmax, 30))
+
+
 if __name__ == "__main__":
     test_nested_name_accesses()
     test_nested_offset_access()
@@ -259,3 +302,4 @@ def small_wip_dappy(inp: dc.float64[KLEV+1, KLON, NBLOCKS], out: dc.float64[KLEV
     test_nested_offset_access_nested_dependency_dappy()
     test_access_to_nested_transient()
     test_access_to_nested_transient_dappy()
+    test_issue_1139()

From c83f601f817fbb8e905e0557ec9fbb6756743a33 Mon Sep 17 00:00:00 2001
From: Philipp Schaad <schaad.phil@gmail.com>
Date: Thu, 14 Nov 2024 19:31:45 +0100
Subject: [PATCH 30/33] Fix `pystr_to_symbolic` not correctly interpreting
 constants as boolean values in boolean comparisons (#1756)

Strings like `not ((N > 20) != 0)` (== `Not(Ne(Gt(N, 20), 0))`) were
incorrectly interpreted by `sympy.sympify` as constant "False". This is
a limitation by sympy, which does not assume integer 0 to be a Falsy,
and enforces exact equivalence (or difference) checks with `Ne`. To get
around this limitation, the DaCe internal AST preprocessor now replaces
constants with boolean values if they are arguments to Comparison
operations, where the other operand is also a comparison operation, thus
returning a boolean.

This fixes an issue with `DeadStateElimination`, closing issue #1129.
---
 dace/symbolic.py                           | 36 +++++++++++++++++++++-
 tests/passes/dead_code_elimination_test.py | 23 +++++++++++++-
 2 files changed, 57 insertions(+), 2 deletions(-)

diff --git a/dace/symbolic.py b/dace/symbolic.py
index 9737080c52..98ffa008d3 100644
--- a/dace/symbolic.py
+++ b/dace/symbolic.py
@@ -1,6 +1,7 @@
-# Copyright 2019-2021 ETH Zurich and the DaCe authors. All rights reserved.
+# Copyright 2019-2024 ETH Zurich and the DaCe authors. All rights reserved.
 import ast
 from functools import lru_cache
+import sys
 import sympy
 import pickle
 import re
@@ -982,6 +983,32 @@ def _process_is(elem: Union[Is, IsNot]):
     return expr
 
 
+# Depending on the Python version we need to handle different AST nodes to correctly interpret and detect falsy / truthy
+# values.
+if sys.version_info < (3, 8):
+    _SimpleASTNode = (ast.Constant, ast.Name, ast.NameConstant, ast.Num)
+    _SimpleASTNodeT = Union[ast.Constant, ast.Name, ast.NameConstant, ast.Num]
+
+    def __comp_convert_truthy_falsy(node: _SimpleASTNodeT):
+        if isinstance(node, ast.Num):
+            node_val = node.n
+        elif isinstance(node, ast.Name):
+            node_val = node.id
+        else:
+            node_val = node.value
+        return ast.copy_location(ast.NameConstant(bool(node_val)), node)
+else:
+    _SimpleASTNode = (ast.Constant, ast.Name)
+    _SimpleASTNodeT = Union[ast.Constant, ast.Name]
+
+    def __comp_convert_truthy_falsy(node: _SimpleASTNodeT):
+        return ast.copy_location(ast.Constant(bool(node.value)), node)
+
+# Convert simple AST node (constant) into a falsy / truthy. Anything other than 0, None, and an empty string '' is
+# considered a truthy, while the listed exceptions are considered falsy values - following the semantics of Python's
+# bool() builtin.
+_convert_truthy_falsy = __comp_convert_truthy_falsy
+
 class PythonOpToSympyConverter(ast.NodeTransformer):
     """ 
     Replaces various operations with the appropriate SymPy functions to avoid non-symbolic evaluation.
@@ -1067,6 +1094,13 @@ def visit_Compare(self, node: ast.Compare):
             raise NotImplementedError
         op = node.ops[0]
         arguments = [node.left, node.comparators[0]]
+
+        # Ensure constant values in boolean comparisons are interpreted als booleans.
+        if isinstance(node.left, ast.Compare) and isinstance(node.comparators[0], _SimpleASTNode):
+            arguments[1] = _convert_truthy_falsy(node.comparators[0])
+        elif isinstance(node.left, _SimpleASTNode) and isinstance(node.comparators[0], ast.Compare):
+            arguments[0] = _convert_truthy_falsy(node.left)
+
         func_node = ast.copy_location(ast.Name(id=self._ast_to_sympy_comparators[type(op)], ctx=ast.Load()), node)
         new_node = ast.Call(func=func_node, args=[self.visit(arg) for arg in arguments], keywords=[])
         return ast.copy_location(new_node, node)
diff --git a/tests/passes/dead_code_elimination_test.py b/tests/passes/dead_code_elimination_test.py
index a41a11c4d6..1832ad8321 100644
--- a/tests/passes/dead_code_elimination_test.py
+++ b/tests/passes/dead_code_elimination_test.py
@@ -1,4 +1,4 @@
-# Copyright 2019-2022 ETH Zurich and the DaCe authors. All rights reserved.
+# Copyright 2019-2024 ETH Zurich and the DaCe authors. All rights reserved.
 """ Various tests for dead code elimination passes. """
 
 import numpy as np
@@ -45,6 +45,26 @@ def test_dse_unconditional():
     assert set(sdfg.states()) == {s, s2, e}
 
 
+def test_dse_edge_condition_with_integer_as_boolean_regression():
+    """
+    This is a regression test for issue #1129, which describes dead state elimination incorrectly eliminating interstate
+    edges when integers are used as boolean values in interstate edge conditions. Code taken from issue #1129.
+    """
+    sdfg = dace.SDFG('dse_edge_condition_with_integer_as_boolean_regression')
+    sdfg.add_scalar('N', dtype=dace.int32, transient=True)
+    sdfg.add_scalar('result', dtype=dace.int32)
+    state_init = sdfg.add_state()
+    state_middle = sdfg.add_state()
+    state_end = sdfg.add_state()
+    sdfg.add_edge(state_init, state_end, dace.InterstateEdge(condition='(not ((N > 20) != 0))',
+                                                             assignments={'result': 'N'}))
+    sdfg.add_edge(state_init, state_middle, dace.InterstateEdge(condition='((N > 20) != 0)'))
+    sdfg.add_edge(state_middle, state_end, dace.InterstateEdge(assignments={'result': '20'}))
+
+    res = DeadStateElimination().apply_pass(sdfg, {})
+    assert res is None
+
+
 def test_dde_simple():
 
     @dace.program
@@ -307,6 +327,7 @@ def test_dce_add_type_hint_of_variable(dtype):
 if __name__ == '__main__':
     test_dse_simple()
     test_dse_unconditional()
+    test_dse_edge_condition_with_integer_as_boolean_regression()
     test_dde_simple()
     test_dde_libnode()
     test_dde_access_node_in_scope(False)

From f7576870a2133e9f118085d8860a789a24e8cb6f Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Philip=20M=C3=BCller?=
 <147368808+philip-paul-mueller@users.noreply.github.com>
Date: Fri, 15 Nov 2024 10:11:57 +0100
Subject: [PATCH 31/33] Fixed `dace::math::pi` and `dace::math::nan` on GPU
 (#1759)

Both $\pi$ and `NaN` are implemented as classes in DaCe.
However, these classes where not marked as device, thus they are only
available on the host.

This PR:
- Fixes this for `NaN` and $\pi$.
- Extend the implementation.
- Adds tests for them.
---
 dace/runtime/include/dace/math.h  |   2 +-
 dace/runtime/include/dace/nan.h   | 100 ++++---
 dace/runtime/include/dace/pi.h    | 473 ++++++++++++++++--------------
 dace/runtime/include/dace/types.h |   6 +
 tests/numpy/constants_test.py     | 170 +++++++++++
 5 files changed, 494 insertions(+), 257 deletions(-)
 create mode 100644 tests/numpy/constants_test.py

diff --git a/dace/runtime/include/dace/math.h b/dace/runtime/include/dace/math.h
index 4dae494a8a..9cc131ee62 100644
--- a/dace/runtime/include/dace/math.h
+++ b/dace/runtime/include/dace/math.h
@@ -496,7 +496,7 @@ namespace dace
 {
     namespace math
     {       
-        static DACE_CONSTEXPR typeless_pi pi{};
+        static DACE_CONSTEXPR DACE_HostDev typeless_pi pi{};
         static DACE_CONSTEXPR typeless_nan nan{};
         //////////////////////////////////////////////////////
         template<typename T>
diff --git a/dace/runtime/include/dace/nan.h b/dace/runtime/include/dace/nan.h
index a8d1eb4c52..b4bac93980 100644
--- a/dace/runtime/include/dace/nan.h
+++ b/dace/runtime/include/dace/nan.h
@@ -13,101 +13,119 @@ namespace dace
         // Defines a typeless Pi
         struct typeless_nan
         {
+            DACE_CONSTEXPR DACE_HDFI typeless_nan() noexcept = default;
+            DACE_CONSTEXPR DACE_HDFI typeless_nan(const typeless_nan&) noexcept = default;
+            DACE_CONSTEXPR DACE_HDFI typeless_nan(typeless_nan&&) noexcept = default;
+            DACE_HDFI ~typeless_nan() noexcept = default;
+
+#ifndef DACE_XILINX
+            DACE_CONSTEXPR DACE_HDFI typeless_nan& operator=(const typeless_nan&) noexcept = default;
+            DACE_CONSTEXPR DACE_HDFI typeless_nan& operator=(typeless_nan&&) noexcept = default;
+#endif
+
             operator int() const = delete;
-            operator float() const
+            DACE_CONSTEXPR DACE_HDFI operator float() const
             {
                 return std::numeric_limits<float>::quiet_NaN();
             }
-            operator double() const
+            DACE_CONSTEXPR DACE_HDFI operator double() const
             {
                 return std::numeric_limits<double>::quiet_NaN();
             }
-            operator long double() const
+
+#if !( defined(__CUDACC__) || defined(__HIPCC__) )
+            //There is no long double on the GPU
+            DACE_CONSTEXPR DACE_HDFI operator long double() const
             {
                 return std::numeric_limits<long double>::quiet_NaN();
             }
-            typeless_nan operator+() const
+#endif
+            DACE_CONSTEXPR DACE_HDFI typeless_nan operator+() const
             {
                 return typeless_nan{};
             }
-            typeless_nan operator-() const
+            DACE_CONSTEXPR DACE_HDFI typeless_nan operator-() const
             {
                 return typeless_nan{};
             }
         };
 
         template<typename T>
-        DACE_CONSTEXPR typename std::enable_if<std::is_floating_point<T>::value, typeless_nan>::type
-        operator*(const T&,  const typeless_nan&) { return typeless_nan{}; }
+        DACE_CONSTEXPR DACE_HDFI std::enable_if_t<std::is_floating_point<T>::value || std::is_integral<T>::value, typeless_nan>
+        operator*(const T&,  const typeless_nan&) noexcept { return typeless_nan{}; }
 
         template<typename T>
-        DACE_CONSTEXPR typename std::enable_if<std::is_floating_point<T>::value, typeless_nan>::type
-        operator*(const typeless_nan&,  const T&) { return typeless_nan{}; }
+        DACE_CONSTEXPR DACE_HDFI std::enable_if_t<std::is_floating_point<T>::value || std::is_integral<T>::value, typeless_nan>
+        operator*(const typeless_nan&,  const T&) noexcept { return typeless_nan{}; }
 
-        inline typeless_nan
-        operator*(const typeless_nan&,  const typeless_nan&) { return typeless_nan{}; }
+        DACE_CONSTEXPR DACE_HDFI typeless_nan
+        operator*(const typeless_nan&,  const typeless_nan&) noexcept { return typeless_nan{}; }
 
 
         template<typename T>
-        DACE_CONSTEXPR typename std::enable_if<std::is_floating_point<T>::value, typeless_nan>::type
-        operator+(const T&,  const typeless_nan&) { return typeless_nan{}; }
+        DACE_CONSTEXPR DACE_HDFI std::enable_if_t<std::is_floating_point<T>::value || std::is_integral<T>::value, typeless_nan>
+        operator+(const T&,  const typeless_nan&) noexcept { return typeless_nan{}; }
 
         template<typename T>
-        DACE_CONSTEXPR typename std::enable_if<std::is_floating_point<T>::value, typeless_nan>::type
-        operator+(const typeless_nan&,  const T&) { return typeless_nan{}; }
+        DACE_CONSTEXPR DACE_HDFI std::enable_if_t<std::is_floating_point<T>::value || std::is_integral<T>::value, typeless_nan>
+        operator+(const typeless_nan&,  const T&) noexcept { return typeless_nan{}; }
 
-        inline typeless_nan
-        operator+(const typeless_nan&,  const typeless_nan&) { return typeless_nan{}; }
+        DACE_CONSTEXPR DACE_HDFI typeless_nan
+        operator+(const typeless_nan&,  const typeless_nan&) noexcept { return typeless_nan{}; }
 
 
         template<typename T>
-        DACE_CONSTEXPR typename std::enable_if<std::is_floating_point<T>::value, typeless_nan>::type
-        operator-(const T&,  const typeless_nan&) { return typeless_nan{}; }
+        DACE_CONSTEXPR DACE_HDFI std::enable_if_t<std::is_floating_point<T>::value || std::is_integral<T>::value, typeless_nan>
+        operator-(const T&,  const typeless_nan&) noexcept { return typeless_nan{}; }
 
         template<typename T>
-        DACE_CONSTEXPR typename std::enable_if<std::is_floating_point<T>::value, typeless_nan>::type
-        operator-(const typeless_nan&,  const T&) { return typeless_nan{}; }
+        DACE_CONSTEXPR DACE_HDFI std::enable_if_t<std::is_floating_point<T>::value || std::is_integral<T>::value, typeless_nan>
+        operator-(const typeless_nan&,  const T&) noexcept { return typeless_nan{}; }
 
-        inline typeless_nan
-        operator-(const typeless_nan&,  const typeless_nan&) { return typeless_nan{}; }
+        DACE_CONSTEXPR DACE_HDFI typeless_nan
+        operator-(const typeless_nan&,  const typeless_nan&) noexcept { return typeless_nan{}; }
 
 
         template<typename T>
-        DACE_CONSTEXPR typename std::enable_if<std::is_floating_point<T>::value, typeless_nan>::type
-        operator/(const T&,  const typeless_nan&) { return typeless_nan{}; }
+        DACE_CONSTEXPR DACE_HDFI std::enable_if_t<std::is_floating_point<T>::value || std::is_integral<T>::value, typeless_nan>
+        operator/(const T&,  const typeless_nan&) noexcept { return typeless_nan{}; }
 
         template<typename T>
-        DACE_CONSTEXPR typename std::enable_if<std::is_floating_point<T>::value, typeless_nan>::type
-        operator/(const typeless_nan&,  const T&) { return typeless_nan{}; }
+        DACE_CONSTEXPR DACE_HDFI std::enable_if_t<std::is_floating_point<T>::value || std::is_integral<T>::value, typeless_nan>
+        operator/(const typeless_nan&,  const T&) noexcept { return typeless_nan{}; }
 
-        inline typeless_nan
-        operator/(const typeless_nan&,  const typeless_nan&) { return typeless_nan{}; }
+        DACE_CONSTEXPR DACE_HDFI typeless_nan
+        operator/(const typeless_nan&,  const typeless_nan&) noexcept { return typeless_nan{}; }
 
 
         template<typename T>
-        DACE_CONSTEXPR typename std::enable_if<std::is_floating_point<T>::value, typeless_nan>::type
-        operator%(const T&,  const typeless_nan&) { return typeless_nan{}; }
+        DACE_CONSTEXPR DACE_HDFI std::enable_if_t<std::is_floating_point<T>::value || std::is_integral<T>::value, typeless_nan>
+        operator%(const T&,  const typeless_nan&) noexcept { return typeless_nan{}; }
 
         template<typename T>
-        DACE_CONSTEXPR typename std::enable_if<std::is_floating_point<T>::value, typeless_nan>::type
-        operator%(const typeless_nan&,  const T&) { return typeless_nan{}; }
+        DACE_CONSTEXPR DACE_HDFI std::enable_if_t<std::is_floating_point<T>::value || std::is_integral<T>::value, typeless_nan>
+        operator%(const typeless_nan&,  const T&) noexcept { return typeless_nan{}; }
 
-        inline typeless_nan
-        operator%(const typeless_nan&,  const typeless_nan&) { return typeless_nan{}; }
+        DACE_CONSTEXPR DACE_HDFI typeless_nan
+        operator%(const typeless_nan&,  const typeless_nan&) noexcept { return typeless_nan{}; }
 
-    }
-}
+        DACE_HDFI typeless_nan ipow(const typeless_nan&, const unsigned int&) {
+            return typeless_nan{};
+        }
 
 	//These functions allows to perfrom operations with `typeless_nan` instances.
-#	define FADAPT(F) DACE_CONSTEXPR ::dace::math::typeless_nan F (::dace::math::typeless_nan) { return ::dace::math::typeless_nan{}; }
-#	define FADAPT2(F) template<typename T1> DACE_CONSTEXPR dace::math::typeless_nan F (T1&&, dace::math::typeless_nan) { return ::dace::math::typeless_nan{}; }; \
-			  template<typename T2> DACE_CONSTEXPR dace::math::typeless_nan F (dace::math::typeless_nan, T2&&) { return ::dace::math::typeless_nan{}; }; \
-			  DACE_CONSTEXPR ::dace::math::typeless_nan F (dace::math::typeless_nan, dace::math::typeless_nan) { return ::dace::math::typeless_nan{}; }
+#	define FADAPT(F) DACE_CONSTEXPR DACE_HDFI typeless_nan F (const typeless_nan&) noexcept { return typeless_nan{}; }
+#	define FADAPT2(F) template<typename T1> DACE_CONSTEXPR DACE_HDFI typeless_nan F (T1&&, dace::math::typeless_nan) noexcept { return typeless_nan{}; }; \
+			  template<typename T2> DACE_CONSTEXPR DACE_HDFI typeless_nan F (const typeless_nan&, T2&&) noexcept { return typeless_nan{}; }; \
+			  DACE_CONSTEXPR DACE_HDFI typeless_nan F (const typeless_nan&, const typeless_nan&) noexcept { return typeless_nan{}; }
         FADAPT(tanh); FADAPT(cos); FADAPT(sin); FADAPT(sqrt); FADAPT(tan);
         FADAPT(acos); FADAPT(asin); FADAPT(atan); FADAPT(log); FADAPT(exp);
         FADAPT(floor); FADAPT(ceil); FADAPT(round); FADAPT(abs);
         FADAPT2(max); FADAPT2(min);
 #       undef FADAPT2
 #	undef FADAPT
+    }
+}
+
 
 #endif  // __DACE_NAN_H
diff --git a/dace/runtime/include/dace/pi.h b/dace/runtime/include/dace/pi.h
index 331b8c1636..818a22f6d0 100644
--- a/dace/runtime/include/dace/pi.h
+++ b/dace/runtime/include/dace/pi.h
@@ -2,6 +2,8 @@
 #ifndef __DACE_PI_H
 #define __DACE_PI_H
 
+#include <type_traits>
+
 // Classes that are used to define a typeless Pi
 
 //#define _USE_MATH_DEFINES
@@ -16,233 +18,274 @@ namespace dace
     {
         //////////////////////////////////////////////////////
         // Defines a typeless Pi
-        struct typeless_pi
+
+        template<typename T>
+        struct is_typeless_pi { static constexpr bool value = false; };
+        #define MAKE_TYPELESS_PI(type) template<> struct is_typeless_pi<type> { static constexpr bool value = true; }
+
+        struct typeless_pi;
+
+        /* Represents $m * \pi$. */
+        struct typeless_pi_mult
         {
-            double value() const { return M_PI; }
-            operator int() const
-            {
-                return int(this->value());
-            }
-            operator float() const
-            {
-                return float(this->value());
-            }
-            operator double() const
-            {
-                return double(this->value());
-            }
+            int mult;
+
+            DACE_CONSTEXPR DACE_HDFI typeless_pi_mult(int m): mult(m) {}
+            DACE_CONSTEXPR DACE_HDFI typeless_pi_mult() noexcept: typeless_pi_mult(1) {};
+
+            DACE_CONSTEXPR DACE_HDFI typeless_pi_mult(const typeless_pi&) noexcept: typeless_pi_mult(1) {};
+            DACE_CONSTEXPR DACE_HDFI typeless_pi_mult(const typeless_pi_mult&) noexcept = default;
+            DACE_CONSTEXPR DACE_HDFI typeless_pi_mult(typeless_pi_mult&&) noexcept = default;
+            DACE_HDFI ~typeless_pi_mult() noexcept = default;
+
+#ifndef DACE_XILINX
+            DACE_CONSTEXPR DACE_HDFI typeless_pi_mult& operator=(const typeless_pi_mult&) noexcept = default;
+            DACE_CONSTEXPR DACE_HDFI typeless_pi_mult& operator=(typeless_pi_mult&&) noexcept = default;
+#endif
+
+            template<
+                typename T,
+                typename = std::enable_if_t<std::is_integral<T>::value>
+            >
+            DACE_CONSTEXPR DACE_HDFI operator T() const noexcept
+            { return T(mult * M_PI); }
+
+            DACE_CONSTEXPR DACE_HDFI operator float() const noexcept
+            { return float(mult * M_PI); }
+
+            DACE_CONSTEXPR DACE_HDFI operator double() const noexcept
+            { return mult * M_PI; }
+
+            DACE_CONSTEXPR DACE_HDFI operator long double() const noexcept
+            { return (long double)(mult * M_PI); }
+
+            DACE_CONSTEXPR DACE_HDFI typeless_pi_mult operator+() const noexcept
+            { return *this; }
+
+            DACE_CONSTEXPR DACE_HDFI typeless_pi_mult operator-() const noexcept
+            { return typeless_pi_mult(-this->mult); }
         };
-        struct typeless_pi_mult : typeless_pi
+        MAKE_TYPELESS_PI(typeless_pi_mult);
+
+        /* Represents $\pi$ */
+        struct typeless_pi
         {
-            int mult; typeless_pi_mult(int m = 1) : mult(m) {}
-            double value() const { return mult * M_PI; }
-
-            operator int() const
-            {
-                return int(this->value());
-            }
-            operator float() const
-            {
-                return float(this->value());
-            }
-            operator double() const
-            {
-                return double(this->value());
-            }
+            DACE_CONSTEXPR DACE_HDFI typeless_pi() noexcept = default;
+            DACE_CONSTEXPR DACE_HDFI typeless_pi(const typeless_pi&) noexcept = default;
+            DACE_CONSTEXPR DACE_HDFI typeless_pi(typeless_pi&&) noexcept = default;
+            DACE_HDFI ~typeless_pi() noexcept = default;
+#ifndef DACE_XILINX
+            DACE_CONSTEXPR DACE_HDFI typeless_pi& operator=(const typeless_pi&) noexcept = default;
+            DACE_CONSTEXPR DACE_HDFI typeless_pi& operator=(typeless_pi&&) noexcept = default;
+#endif
+
+            template<
+                typename T,
+                typename = std::enable_if_t<std::is_integral<T>::value>
+            >
+            DACE_CONSTEXPR DACE_HDFI operator T() const noexcept
+            { return T(M_PI); }
+
+            DACE_CONSTEXPR DACE_HDFI operator float() const noexcept
+            { return float(M_PI); }
+
+            DACE_CONSTEXPR DACE_HDFI operator double() const noexcept
+            { return M_PI; }
+
+            DACE_CONSTEXPR DACE_HDFI operator long double() const noexcept
+            { return (long double)(M_PI); }
+
+            DACE_CONSTEXPR DACE_HDFI typeless_pi operator+() const noexcept
+            { return *this; }
+
+            DACE_CONSTEXPR DACE_HDFI typeless_pi_mult operator-() const noexcept
+            { return typeless_pi_mult(-1); }
         };
-        struct typeless_pi_exp : typeless_pi_mult
+        MAKE_TYPELESS_PI(typeless_pi);
+
+        /* Represents $m * \pi^{e}$ */
+        struct typeless_pi_exp
         {
-            int mult, exp; typeless_pi_exp(int m = 1, int e = 1) : mult(m), exp(e) {}
-            double value() const { return mult * std::pow(M_PI, exp); }
-            operator int() const
-            {
-                return int(this->value());
-            }
-            operator float() const
-            {
-                return float(this->value());
-            }
-            operator double() const
-            {
-                return double(this->value());
-            }
+            int mult, exp;
+
+            DACE_CONSTEXPR DACE_HDFI typeless_pi_exp(int m, int e): mult(m), exp(e) {}
+            DACE_CONSTEXPR DACE_HDFI typeless_pi_exp() noexcept: typeless_pi_exp(1, 1) {};
+
+            DACE_CONSTEXPR DACE_HDFI typeless_pi_exp(const typeless_pi_exp&) noexcept = default;
+            DACE_CONSTEXPR DACE_HDFI typeless_pi_exp(typeless_pi_exp&&) noexcept = default;
+            DACE_HDFI ~typeless_pi_exp() noexcept = default;
+
+#ifndef DACE_XILINX
+            DACE_CONSTEXPR DACE_HDFI typeless_pi_exp& operator=(const typeless_pi_exp&) noexcept = default;
+            DACE_CONSTEXPR DACE_HDFI typeless_pi_exp& operator=(typeless_pi_exp&&) noexcept = default;
+#endif
+
+            template<
+                typename T,
+                typename = std::enable_if_t<std::is_integral<T>::value>
+            >
+            DACE_CONSTEXPR DACE_HDFI operator T() const noexcept
+            { return T(mult * std::pow(static_cast<T>(M_PI), exp)); }
+
+
+            /* We have to do the selection this way, because it seems as nvidia does
+             *  not provide `powl` and `powf` in the std namespace */
+            DACE_CONSTEXPR DACE_HDFI operator float() const
+            { using std::pow; return mult * pow(static_cast<float>(M_PI), exp); }
+
+            DACE_CONSTEXPR DACE_HDFI operator double() const
+            { using std::pow; return mult * std::pow(static_cast<double>(M_PI), exp); }
+
+#if !( defined(__CUDACC__) || defined(__HIPCC__) )
+            //There is no long double on the GPU
+            DACE_CONSTEXPR DACE_HDFI operator long double() const
+            { using std::pow; return mult * std::pow(static_cast<long double>(M_PI), exp); }
+#endif
+
+            DACE_CONSTEXPR DACE_HDFI typeless_pi_exp operator+() const
+            { return *this; }
+
+            DACE_CONSTEXPR DACE_HDFI typeless_pi_exp operator-() const
+            { return typeless_pi_exp(-this->mult, this->exp); }
         };
-        inline typeless_pi_mult operator*(const typeless_pi&, const int& num)
-        {
-            return typeless_pi_mult(num);
-        }
-        inline typeless_pi_mult operator*(const typeless_pi_mult& p, const int& num)
-        {
-            return typeless_pi_mult(p.mult * num);
-        }
-        inline typeless_pi_exp operator*(const typeless_pi_exp& p, const int& num)
-        {
-            return typeless_pi_exp(p.mult * num, p.exp);
-        }
-        inline typeless_pi_mult operator*(const int& num, const typeless_pi&)
-        {
-            return typeless_pi_mult(num);
-        }
-        inline typeless_pi_mult operator*(const int& num, const typeless_pi_mult& p)
-        {
-            return typeless_pi_mult(num * p.mult);
-        }
-        inline typeless_pi_exp operator*(const int& num, const typeless_pi_exp& p)
-        {
-            return typeless_pi_exp(num * p.mult, p.exp);
-        }
-        template <typename T>
-        T operator+(const typeless_pi& p, const T& num)
-        {
-            return T(p.value()) + num;
-        }
-        template <typename T>
-        T operator-(const typeless_pi& p, const T& num)
-        {
-            return T(p.value()) - num;
-        }
+        MAKE_TYPELESS_PI(typeless_pi_exp);
 
-        template <typename T>
-        T operator*(const typeless_pi& p, const T& num)
-        {
-            return T(p.value()) * num;
-        }
-        template <typename T>
-        T operator/(const typeless_pi& p, const T& num)
-        {
-            return T(p.value()) / num;
-        }
-        template <typename T>
-        T operator+(const T& num, const typeless_pi& p)
-        {
-            return num + T(p.value());
-        }
-        template <typename T>
-        T operator-(const T& num, const typeless_pi& p)
-        {
-            return num - T(p.value());
-        }
-        template <typename T>
-        T operator*(const T& num, const typeless_pi& p)
-        {
-            return num * T(p.value());
-        }
-        template <typename T>
-        T operator/(const T& num, const typeless_pi& p)
-        {
-            return num / T(p.value());
-        }
-        template <typename T>
-        T operator+(const typeless_pi_mult& p, const T& num)
-        {
-            return T(p.value()) + num;
-        }
-        template <typename T>
-        T operator-(const typeless_pi_mult& p, const T& num)
-        {
-            return T(p.value()) - num;
-        }
 
-        template <typename T>
-        T operator*(const typeless_pi_mult& p, const T& num)
-        {
-            return T(p.value()) * num;
-        }
-        template <typename T>
-        T operator/(const typeless_pi_mult& p, const T& num)
-        {
-            return T(p.value()) / num;
-        }
-        template <typename T>
-        T operator+(const T& num, const typeless_pi_mult& p)
-        {
-            return num + T(p.value());
-        }
-        template <typename T>
-        T operator-(const T& num, const typeless_pi_mult& p)
-        {
-            return num - T(p.value());
-        }
-        template <typename T>
-        T operator*(const T& num, const typeless_pi_mult& p)
-        {
-            return num * T(p.value());
-        }
-        template <typename T>
-        T operator/(const T& num, const typeless_pi_mult& p)
-        {
-            return num / T(p.value());
-        }
-        template <typename T>
-        T operator+(const typeless_pi_exp& p, const T& num)
-        {
-            return T(p.value()) + num;
-        }
-        template <typename T>
-        T operator-(const typeless_pi_exp& p, const T& num)
-        {
-            return T(p.value()) - num;
-        }
+        DACE_CONSTEXPR DACE_HDFI int operator/(const typeless_pi&, const typeless_pi&) noexcept
+        { return 1; }
 
-        template <typename T>
-        T operator*(const typeless_pi_exp& p, const T& num)
-        {
-            return T(p.value()) * num;
-        }
-        template <typename T>
-        T operator/(const typeless_pi_exp& p, const T& num)
-        {
-            return T(p.value()) / num;
-        }
-        template <typename T>
-        T operator+(const T& num, const typeless_pi_exp& p)
-        {
-            return num + T(p.value());
-        }
-        template <typename T>
-        T operator-(const T& num, const typeless_pi_exp& p)
-        {
-            return num - T(p.value());
-        }
-        template <typename T>
-        T operator*(const T& num, const typeless_pi_exp& p)
-        {
-            return num * T(p.value());
-        }
-        template <typename T>
-        T operator/(const T& num, const typeless_pi_exp& p)
-        {
-            return num / T(p.value());
-        }
-        inline typeless_pi_mult operator-(const typeless_pi&)
-        {
-            return typeless_pi_mult(-1);
-        }
-        template <typename T>
-        typeless_pi_mult operator+(const typeless_pi&, const typeless_pi&)
-        {
-            return typeless_pi_mult(2);
-        }
-        template <typename T>
-        typeless_pi_mult operator+(const typeless_pi_mult& p1, const typeless_pi_mult& p2)
-        {
-            return typeless_pi_mult(p1.mult + p2.mult);
-        }
-        template <typename T>
-        typeless_pi_exp operator*(const typeless_pi_mult& p1, const typeless_pi_mult& p2)
-        {
-            return typeless_pi_exp(p1.mult * p2.mult, 2);
+        DACE_CONSTEXPR DACE_HDFI int operator-(const typeless_pi&, const typeless_pi&) noexcept
+        { return 0; }
+
+
+        DACE_CONSTEXPR DACE_HDFI typeless_pi_mult operator*(const typeless_pi&, const int& num) noexcept
+        { return typeless_pi_mult(num); }
+
+        DACE_CONSTEXPR DACE_HDFI typeless_pi_mult operator*(const int& num, const typeless_pi&) noexcept
+        { return typeless_pi_mult(num); }
+
+        DACE_CONSTEXPR DACE_HDFI typeless_pi_mult operator*(const typeless_pi_mult& p, const int& num) noexcept
+        { return typeless_pi_mult(p.mult * num); }
+
+        DACE_CONSTEXPR DACE_HDFI typeless_pi_mult operator*(const int& num, const typeless_pi_mult& p) noexcept
+        { return typeless_pi_mult(p.mult * num); }
+
+        DACE_CONSTEXPR DACE_HDFI typeless_pi_mult operator+(const typeless_pi&, const typeless_pi&) noexcept
+        { return typeless_pi_mult(2); }
+
+        DACE_CONSTEXPR DACE_HDFI typeless_pi_mult operator+(const typeless_pi&, const typeless_pi_mult& pi) noexcept
+        { return typeless_pi_mult(pi.mult + 1); }
+
+        DACE_CONSTEXPR DACE_HDFI typeless_pi_mult operator+(const typeless_pi_mult& pi, const typeless_pi&) noexcept
+        { return typeless_pi_mult(pi.mult + 1); }
+
+        DACE_CONSTEXPR DACE_HDFI typeless_pi_mult operator+(const typeless_pi_mult& pl, const typeless_pi_mult& pr) noexcept
+        { return typeless_pi_mult(pl.mult + pr.mult); }
+
+        DACE_CONSTEXPR DACE_HDFI typeless_pi_mult operator-(const typeless_pi_mult& pl, const typeless_pi_mult& pr) noexcept
+        { return typeless_pi_mult(pl.mult - pr.mult); }
+
+        DACE_CONSTEXPR DACE_HDFI int operator/(const typeless_pi_mult& pl, const typeless_pi&) noexcept
+        { return pl.mult; }
+
+        DACE_CONSTEXPR DACE_HDFI double operator/(const typeless_pi& pl, const typeless_pi_mult& pr) noexcept
+        { return 1.0 / pr.mult; }
+
+
+
+        DACE_CONSTEXPR DACE_HDFI typeless_pi_exp operator*(const typeless_pi&, const typeless_pi&) noexcept
+        { return typeless_pi_exp(1, 2); }
+
+        DACE_CONSTEXPR DACE_HDFI typeless_pi_exp operator*(const typeless_pi_mult& pl, const typeless_pi_mult& pr) noexcept
+        { return typeless_pi_exp(pl.mult * pr.mult, 2); }
+
+        DACE_CONSTEXPR DACE_HDFI typeless_pi_exp operator*(const typeless_pi_mult& pl, const typeless_pi&) noexcept
+        { return typeless_pi_exp(pl.mult, 2); }
+
+        DACE_CONSTEXPR DACE_HDFI typeless_pi_exp operator*(const typeless_pi& pl, const typeless_pi_mult& pr) noexcept
+        { return typeless_pi_exp(pr.mult, 2); }
+
+        DACE_CONSTEXPR DACE_HDFI typeless_pi_exp operator*(const typeless_pi_exp& pl, const typeless_pi_mult& pr) noexcept
+        { return typeless_pi_exp(pl.mult * pr.mult, pl.exp + 1); }
+
+        DACE_CONSTEXPR DACE_HDFI typeless_pi_exp operator*(const typeless_pi_mult& pl, const typeless_pi_exp& pr) noexcept
+        { return pr * pl; }
+
+        DACE_CONSTEXPR DACE_HDFI typeless_pi_exp operator*(const typeless_pi_exp& pl, const typeless_pi_exp& pr) noexcept
+        { return typeless_pi_exp(pl.mult * pr.mult, pr.exp + pl.exp); }
+
+        DACE_CONSTEXPR DACE_HDFI typeless_pi_exp operator*(const typeless_pi_exp& pl, const int& num) noexcept
+        { return typeless_pi_exp(pl.mult * num, pl.exp); }
+
+        DACE_CONSTEXPR DACE_HDFI typeless_pi_exp operator*(const int& num, const typeless_pi_exp& pr) noexcept
+        { return typeless_pi_exp(pr.mult * num, pr.exp); }
+
+        DACE_CONSTEXPR DACE_HDFI typeless_pi_exp operator/(const typeless_pi_exp& pl, const typeless_pi&) noexcept
+        { return typeless_pi_exp(pl.mult, pl.exp - 1); }
+
+
+        // The code generator guarantees us that `b > 0`.
+        DACE_HDFI typeless_pi_exp ipow(const typeless_pi_mult& pi, const unsigned int& b) {
+            return typeless_pi_exp(pow(pi.mult, b), b);
         }
-        template <typename T>
-        typeless_pi_exp operator*(const typeless_pi&, const typeless_pi&)
-        {
-            return typeless_pi_exp(1, 2);
+        DACE_HDFI typeless_pi_exp ipow(const typeless_pi& pi, const unsigned int& b) {
+            return typeless_pi_exp(1, b);
         }
-        template <typename T>
-        typeless_pi_exp operator*(const typeless_pi_exp& p1, const typeless_pi_exp& p2)
-        {
-            return typeless_pi_exp(p1.mult * p2.mult, p1.exp + p2.exp);
+        DACE_HDFI typeless_pi_exp ipow(const typeless_pi_exp& pi, const unsigned int& b) {
+            return typeless_pi_exp(pow(pi.mult, b), pi.exp * b);
         }
+
+#       define DEF_PI_OPS(op) 										\
+	template<typename T, typename PI, typename = std::enable_if_t<is_typeless_pi<PI>::value && (!is_typeless_pi<T>::value)> >	\
+	DACE_CONSTEXPR DACE_HDFI T operator op (const T& lhs, const PI& pi) noexcept			\
+	{ return lhs op (static_cast<T>(pi)); }								\
+	template<typename PI, typename T, typename = std::enable_if_t<is_typeless_pi<PI>::value && (!is_typeless_pi<T>::value)> >	\
+	DACE_CONSTEXPR DACE_HDFI T operator op (const PI& pi, const T& rhs) noexcept			\
+	{ return (static_cast<T>(pi)) op rhs; }
+
+	DEF_PI_OPS(+);
+	DEF_PI_OPS(-);
+	DEF_PI_OPS(/);
+	DEF_PI_OPS(*);
+
+        DACE_CONSTEXPR DACE_HDFI int sin(const typeless_pi&) noexcept
+        { return 0; }
+
+        DACE_CONSTEXPR DACE_HDFI int sin(const typeless_pi_mult& pi) noexcept
+        { return 0; }
+
+	DACE_HDFI double sin(const typeless_pi_exp& pi) noexcept
+	{ return std::sin(static_cast<double>(pi)); }
+
+        DACE_CONSTEXPR DACE_HDFI int cos(const typeless_pi&) noexcept
+        { return 1; }
+
+        DACE_CONSTEXPR DACE_HDFI int cos(const typeless_pi_mult& pi) noexcept
+        { return (pi.mult % 2 == 0) ? 1 : (-1); }
+
+	DACE_HDFI double cos(const typeless_pi_exp& pi) noexcept
+	{ return std::cos(static_cast<double>(pi)); }
+
+
+#       define DEF_PI_TRIGO(F)						\
+	DACE_HDFI double F (const typeless_pi& pi) noexcept		\
+	{ return std:: F( static_cast<double>(pi) ); }			\
+	DACE_HDFI double F (const typeless_pi_mult& pi) noexcept	\
+	{ return std:: F( static_cast<double>(pi) ); }			\
+	DACE_HDFI double F (const typeless_pi_exp& pi) noexcept		\
+	{ return std:: F( static_cast<double>(pi) ); }
+
+        DEF_PI_TRIGO(asin);
+        DEF_PI_TRIGO(acos);
+        DEF_PI_TRIGO(tan);
+        DEF_PI_TRIGO(atan);
+        DEF_PI_TRIGO(exp);
+        DEF_PI_TRIGO(log);
+
+
+#       undef DEF_PI_TRIGO
+#       undef DEF_PI_OPS
+#	undef MAKE_TYPELESS_PI
     }
 }
 
diff --git a/dace/runtime/include/dace/types.h b/dace/runtime/include/dace/types.h
index e5eed1e35e..9a8676e0d4 100644
--- a/dace/runtime/include/dace/types.h
+++ b/dace/runtime/include/dace/types.h
@@ -49,7 +49,13 @@
     #define DACE_HDFI __host__ __device__ __forceinline__
     #define DACE_HFI __host__ __forceinline__
     #define DACE_DFI __device__ __forceinline__
+    #define DACE_HostDev __host__ __device__
+    #define DACE_Host __host__ 
+    #define DACE_Dev __device__
 #else
+    #define DACE_HostDev
+    #define DACE_Host 
+    #define DACE_Dev
     #define DACE_HDFI inline
     #define DACE_HFI inline
     #define DACE_DFI inline
diff --git a/tests/numpy/constants_test.py b/tests/numpy/constants_test.py
new file mode 100644
index 0000000000..6aa3b15621
--- /dev/null
+++ b/tests/numpy/constants_test.py
@@ -0,0 +1,170 @@
+# Copyright 2019-2024 ETH Zurich and the DaCe authors. All rights reserved.
+import dace
+import numpy as np
+import uuid
+import math
+import pytest
+
+def _make_sdfg(
+        code: str,
+        dtype = dace.float64,
+) -> dace.SDFG:
+    """Generates an SDFG that writes an expression to an array.
+    """
+    sdfg = dace.SDFG(name=f"const_test_{str(uuid.uuid1()).replace('-', '_')}")
+    state = sdfg.add_state(is_start_block=True)
+    sdfg.add_array(
+            "out",
+            shape=(10,),
+            dtype=dtype,
+            transient=False,
+    )
+
+    state.add_mapped_tasklet(
+            "comput",
+            map_ranges={"__i": "0:10"},
+            inputs={},
+            code=f"__out = {code}",
+            outputs={"__out": dace.Memlet("out[__i]")},
+            external_edges=True,
+    )
+    sdfg.validate()
+    return sdfg
+
+
+def _test_sdfg(
+        sdfg: dace.SDFG,
+        expected,
+        dtype = np.float64,
+):
+    out = np.zeros(10, dtype=dtype)
+    sdfg.apply_gpu_transformations()
+    sdfg(out=out)
+    assert np.allclose(out, expected, equal_nan=True), f"Expected {expected}, but got {out[0]}"
+
+
+def _perform_test(
+        code,
+        expected,
+        dtype = np.float64,
+):
+    print(f"PERFORM: {code}")
+    dace_dtype = dace.dtypes.dtype_to_typeclass(dtype)
+    sdfg = _make_sdfg(code=code, dtype=dace_dtype)
+    _test_sdfg(sdfg=sdfg, expected=expected, dtype=dtype)
+
+
+@pytest.mark.gpu
+def test_constant_pi_simple():
+    _perform_test(
+            code="math.pi",
+            expected=math.pi
+    )
+
+
+@pytest.mark.gpu
+def test_constant_pi_add():
+    _perform_test(
+            code="-math.pi",
+            expected=-math.pi
+    )
+    _perform_test(
+            code="math.pi + math.pi",
+            expected=2 * math.pi
+    )
+    _perform_test(
+            code="math.pi - math.pi",
+            expected=0.
+    )
+
+
+@pytest.mark.gpu
+def test_constant_pi_mult():
+    _perform_test(
+            code="(math.pi ** 2) * 2",
+            expected=math.pi * math.pi * 2.0
+    )
+    _perform_test(
+            code="math.pi * 2",
+            expected=2 * math.pi
+    )
+    _perform_test(
+            code="math.pi * 2 + math.pi",
+            expected=2 * math.pi + math.pi
+    )
+    _perform_test(
+            code="math.pi * math.pi * 2",
+            expected=math.pi * math.pi * 2.0
+    )
+    _perform_test(
+            code="math.pi / math.pi ",
+            expected=1
+    )
+    _perform_test(
+            code="(math.pi + math.pi) / math.pi ",
+            expected=2
+    )
+    _perform_test(
+            code="(math.pi * math.pi) / math.pi ",
+            expected=math.pi
+    )
+
+
+@pytest.mark.gpu
+def test_constant_pi_fun():
+    _perform_test(
+            code="math.sin(math.pi)",
+            expected=0,
+    )
+    _perform_test(
+            code="math.sin(math.pi * 4)",
+            expected=math.sin(math.pi * 4),
+    )
+    _perform_test(
+            code="math.sin(math.pi * 5)",
+            expected=math.sin(math.pi * 5),
+    )
+    _perform_test(
+            code="math.cos(math.pi * 4)",
+            expected=math.cos(math.pi * 4),
+    )
+    _perform_test(
+            code="math.cos(math.pi * 5)",
+            expected=math.cos(math.pi * 5),
+    )
+    _perform_test(
+            code="math.log(math.pi)",
+            expected=math.log(math.pi),
+    )
+
+
+@pytest.mark.gpu
+def test_constant_nan():
+    _perform_test(
+            code="math.nan",
+            expected=math.nan
+    )
+    _perform_test(
+            code="math.nan + 2",
+            expected=math.nan
+    )
+    _perform_test(
+            code="math.nan + 2.0",
+            expected=math.nan
+    )
+    _perform_test(
+            code="math.sin(math.nan + 2.0)",
+            expected=math.nan
+    )
+    _perform_test(
+            code="math.sin(math.nan + 2.0) ** 2",
+            expected=math.nan
+    )
+
+
+if __name__ == "__main__":
+    test_constant_pi_simple()
+    test_constant_pi_add()
+    test_constant_pi_mult()
+    test_constant_pi_fun()
+    test_constant_nan()

From b5f91e18c3ff6b599793645507f54a68b3f07c1f Mon Sep 17 00:00:00 2001
From: Tal Ben-Nun <tbennun@users.noreply.github.com>
Date: Fri, 15 Nov 2024 10:29:14 -0800
Subject: [PATCH 32/33] Make scalar to symbol promotion robust to node order in
 state (#1766)

Fixes #1727
---
 dace/sdfg/analysis/schedule_tree/treenodes.py |  2 ++
 .../transformation/passes/scalar_to_symbol.py |  4 ++-
 tests/passes/scalar_to_symbol_test.py         | 30 +++++++++++++++++++
 3 files changed, 35 insertions(+), 1 deletion(-)

diff --git a/dace/sdfg/analysis/schedule_tree/treenodes.py b/dace/sdfg/analysis/schedule_tree/treenodes.py
index 3b447fa15a..dabd436b56 100644
--- a/dace/sdfg/analysis/schedule_tree/treenodes.py
+++ b/dace/sdfg/analysis/schedule_tree/treenodes.py
@@ -41,6 +41,8 @@ def __init__(self, children: Optional[List['ScheduleTreeNode']] = None):
         if self.children:
             for child in children:
                 child.parent = self
+        self.containers = {}
+        self.symbols = {}
 
     def as_string(self, indent: int = 0):
         if not self.children:
diff --git a/dace/transformation/passes/scalar_to_symbol.py b/dace/transformation/passes/scalar_to_symbol.py
index 33712c8a1c..a37729ca7c 100644
--- a/dace/transformation/passes/scalar_to_symbol.py
+++ b/dace/transformation/passes/scalar_to_symbol.py
@@ -522,6 +522,8 @@ def remove_scalar_reads(sdfg: sd.SDFG, array_names: Dict[str, str]):
     for state in sdfg.states():
         scalar_nodes = [n for n in state.nodes() if isinstance(n, nodes.AccessNode) and n.data in array_names]
         for node in scalar_nodes:
+            if node not in state:
+                continue
             symname = array_names[node.data]
             for out_edge in state.out_edges(node):
                 for e in state.memlet_tree(out_edge):
@@ -649,7 +651,7 @@ def apply_pass(self, sdfg: SDFG, _: Dict[Any, Any]) -> Set[str]:
             scalar_nodes = [n for n in state.nodes() if isinstance(n, nodes.AccessNode) and n.data in to_promote]
             # Step 2: Assignment tasklets
             for node in scalar_nodes:
-                if state.in_degree(node) == 0:
+                if node not in state or state.in_degree(node) == 0:
                     continue
                 in_edge = state.in_edges(node)[0]
                 input = in_edge.src
diff --git a/tests/passes/scalar_to_symbol_test.py b/tests/passes/scalar_to_symbol_test.py
index 7fdfbdf737..36decceba2 100644
--- a/tests/passes/scalar_to_symbol_test.py
+++ b/tests/passes/scalar_to_symbol_test.py
@@ -729,6 +729,35 @@ def test_double_index_bug():
                         assert getattr(sympy_node, "name", None) != "indices"
 
 
+def test_reversed_order():
+    """
+    Tests a failure reported in issue #1727.
+    """
+    sdfg = dace.SDFG('tester')
+    sdfg.add_array('inputs', [1], dace.int32)
+    sdfg.add_transient('a', [1], dace.int32)
+    sdfg.add_transient('b', [1], dace.int32)
+    sdfg.add_array('output', [1], dace.int32)
+    initstate = sdfg.add_state()
+    state = sdfg.add_state_after(initstate)
+    finistate = sdfg.add_state_after(state)
+
+    # Note the order here
+    w = state.add_write('b')
+    t = state.add_tasklet('assign', {'inp'}, {'out'}, 'out = inp')
+    r = state.add_read('a')
+    state.add_edge(t, 'out', w, None, dace.Memlet('b'))
+    state.add_edge(r, None, t, 'inp', dace.Memlet('a'))
+
+    initstate.add_nedge(initstate.add_read('inputs'), initstate.add_write('a'), dace.Memlet('inputs'))
+    finistate.add_nedge(finistate.add_read('b'), finistate.add_write('output'), dace.Memlet('output'))
+
+    sdfg.validate()
+    promoted = scalar_to_symbol.ScalarToSymbolPromotion().apply_pass(sdfg, {})
+    assert promoted == {'a', 'b'}
+    sdfg.compile()
+
+
 if __name__ == '__main__':
     test_find_promotable()
     test_promote_simple()
@@ -753,3 +782,4 @@ def test_double_index_bug():
     test_ternary_expression(False)
     test_ternary_expression(True)
     test_double_index_bug()
+    test_reversed_order()

From 4f8eb9225e11aef2c8111628423bc0a847caf224 Mon Sep 17 00:00:00 2001
From: Tal Ben-Nun <tbennun@gmail.com>
Date: Fri, 15 Nov 2024 23:30:07 -0800
Subject: [PATCH 33/33] Match CMake version requirements

---
 setup.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/setup.py b/setup.py
index c228ae4558..9c9bc020bb 100644
--- a/setup.py
+++ b/setup.py
@@ -38,7 +38,7 @@
         output = subprocess.check_output([cmake_path, '--version']).decode('utf-8')
         cmake_version = tuple(int(t) for t in output.splitlines()[0].split(' ')[-1].split('.'))
         # If version meets minimum requirements, CMake is not necessary
-        if cmake_version >= (3, 15):
+        if cmake_version >= (3, 17):
             cmake_requires = []
 except (subprocess.CalledProcessError, OSError, IndexError, ValueError):
     # Any failure in getting the CMake version counts as "not found"