Fix merge conflicts

.devcontainer/cuda12.2-conda/devcontainer.json → .devcontainer/cuda12.5-conda/devcontainer.json

@@ -3,15 +3,15 @@
     "context": "${localWorkspaceFolder}/.devcontainer",
     "dockerfile": "${localWorkspaceFolder}/.devcontainer/Dockerfile",
     "args": {
-      "CUDA": "12.2",
+      "CUDA": "12.5",
       "PYTHON_PACKAGE_MANAGER": "conda",
       "BASE": "rapidsai/devcontainers:24.08-cpp-mambaforge-ubuntu22.04"
     }
   },
   "runArgs": [
     "--rm",
     "--name",
-    "${localEnv:USER:anon}-rapids-${localWorkspaceFolderBasename}-24.08-cuda12.2-conda"
+    "${localEnv:USER:anon}-rapids-${localWorkspaceFolderBasename}-24.08-cuda12.5-conda"
   ],
   "hostRequirements": {"gpu": "optional"},
   "features": {
@@ -20,7 +20,7 @@
   "overrideFeatureInstallOrder": [
     "ghcr.io/rapidsai/devcontainers/features/rapids-build-utils"
   ],
-  "initializeCommand": ["/bin/bash", "-c", "mkdir -m 0755 -p ${localWorkspaceFolder}/../.{aws,cache,config,conda/pkgs,conda/${localWorkspaceFolderBasename}-cuda12.2-envs}"],
+  "initializeCommand": ["/bin/bash", "-c", "mkdir -m 0755 -p ${localWorkspaceFolder}/../.{aws,cache,config,conda/pkgs,conda/${localWorkspaceFolderBasename}-cuda12.5-envs}"],
   "postAttachCommand": ["/bin/bash", "-c", "if [ ${CODESPACES:-false} = 'true' ]; then . devcontainer-utils-post-attach-command; . rapids-post-attach-command; fi"],
   "workspaceFolder": "/home/coder",
   "workspaceMount": "source=${localWorkspaceFolder},target=/home/coder/cudf,type=bind,consistency=consistent",
@@ -29,7 +29,7 @@
     "source=${localWorkspaceFolder}/../.cache,target=/home/coder/.cache,type=bind,consistency=consistent",
     "source=${localWorkspaceFolder}/../.config,target=/home/coder/.config,type=bind,consistency=consistent",
     "source=${localWorkspaceFolder}/../.conda/pkgs,target=/home/coder/.conda/pkgs,type=bind,consistency=consistent",
-    "source=${localWorkspaceFolder}/../.conda/${localWorkspaceFolderBasename}-cuda12.2-envs,target=/home/coder/.conda/envs,type=bind,consistency=consistent"
+    "source=${localWorkspaceFolder}/../.conda/${localWorkspaceFolderBasename}-cuda12.5-envs,target=/home/coder/.conda/envs,type=bind,consistency=consistent"
   ],
   "customizations": {
     "vscode": {

.devcontainer/cuda12.2-pip/devcontainer.json → .devcontainer/cuda12.5-pip/devcontainer.json

@@ -3,15 +3,15 @@
     "context": "${localWorkspaceFolder}/.devcontainer",
     "dockerfile": "${localWorkspaceFolder}/.devcontainer/Dockerfile",
     "args": {
-      "CUDA": "12.2",
+      "CUDA": "12.5",
       "PYTHON_PACKAGE_MANAGER": "pip",
-      "BASE": "rapidsai/devcontainers:24.08-cpp-cuda12.2-ubuntu22.04"
+      "BASE": "rapidsai/devcontainers:24.08-cpp-cuda12.5-ubuntu22.04"
     }
   },
   "runArgs": [
     "--rm",
     "--name",
-    "${localEnv:USER:anon}-rapids-${localWorkspaceFolderBasename}-24.08-cuda12.2-pip"
+    "${localEnv:USER:anon}-rapids-${localWorkspaceFolderBasename}-24.08-cuda12.5-pip"
   ],
   "hostRequirements": {"gpu": "optional"},
   "features": {
@@ -20,15 +20,15 @@
   "overrideFeatureInstallOrder": [
     "ghcr.io/rapidsai/devcontainers/features/rapids-build-utils"
   ],
-  "initializeCommand": ["/bin/bash", "-c", "mkdir -m 0755 -p ${localWorkspaceFolder}/../.{aws,cache,config/pip,local/share/${localWorkspaceFolderBasename}-cuda12.2-venvs}"],
+  "initializeCommand": ["/bin/bash", "-c", "mkdir -m 0755 -p ${localWorkspaceFolder}/../.{aws,cache,config/pip,local/share/${localWorkspaceFolderBasename}-cuda12.5-venvs}"],
   "postAttachCommand": ["/bin/bash", "-c", "if [ ${CODESPACES:-false} = 'true' ]; then . devcontainer-utils-post-attach-command; . rapids-post-attach-command; fi"],
   "workspaceFolder": "/home/coder",
   "workspaceMount": "source=${localWorkspaceFolder},target=/home/coder/cudf,type=bind,consistency=consistent",
   "mounts": [
     "source=${localWorkspaceFolder}/../.aws,target=/home/coder/.aws,type=bind,consistency=consistent",
     "source=${localWorkspaceFolder}/../.cache,target=/home/coder/.cache,type=bind,consistency=consistent",
     "source=${localWorkspaceFolder}/../.config,target=/home/coder/.config,type=bind,consistency=consistent",
-    "source=${localWorkspaceFolder}/../.local/share/${localWorkspaceFolderBasename}-cuda12.2-venvs,target=/home/coder/.local/share/venvs,type=bind,consistency=consistent"
+    "source=${localWorkspaceFolder}/../.local/share/${localWorkspaceFolderBasename}-cuda12.5-venvs,target=/home/coder/.local/share/venvs,type=bind,consistency=consistent"
   ],
   "customizations": {
     "vscode": {

.github/workflows/pandas-tests.yaml

@@ -19,7 +19,7 @@ jobs:
       secrets: inherit
       uses: rapidsai/shared-workflows/.github/workflows/[email protected]
       with:
-        matrix_filter: map(select(.ARCH == "amd64" and .PY_VER == "3.9" and .CUDA_VER == "12.2.2" ))
+        matrix_filter: map(select(.ARCH == "amd64" and .PY_VER == "3.9" and (.CUDA_VER | startswith("12.5.")) ))
         build_type: nightly
         branch: ${{ inputs.branch }}
         date: ${{ inputs.date }}

.github/workflows/pr.yaml

@@ -177,7 +177,7 @@ jobs:
     uses: rapidsai/shared-workflows/.github/workflows/[email protected]
     with:
       arch: '["amd64"]'
-      cuda: '["12.2"]'
+      cuda: '["12.5"]'
       build_command: |
         sccache -z;
         build-all -DBUILD_BENCHMARKS=ON --verbose;
@@ -196,7 +196,7 @@ jobs:
     secrets: inherit
     uses: rapidsai/shared-workflows/.github/workflows/[email protected]
     with:
-      matrix_filter: map(select(.ARCH == "amd64" and .PY_VER == "3.9" and .CUDA_VER == "12.2.2" ))
+      matrix_filter: map(select(.ARCH == "amd64" and .PY_VER == "3.9" and (.CUDA_VER | startswith("12.5.")) ))
       build_type: pull-request
       script: ci/cudf_pandas_scripts/pandas-tests/run.sh pr
       # Hide test failures because they exceed the GITHUB_STEP_SUMMARY output limit.

CONTRIBUTING.md

@@ -104,7 +104,7 @@ Instructions for a minimal build environment without conda are included below.
 # create the conda environment (assuming in base `cudf` directory)
 # note: RAPIDS currently doesn't support `channel_priority: strict`;
 # use `channel_priority: flexible` instead
-conda env create --name cudf_dev --file conda/environments/all_cuda-122_arch-x86_64.yaml
+conda env create --name cudf_dev --file conda/environments/all_cuda-125_arch-x86_64.yaml
 # activate the environment
 conda activate cudf_dev
 ```

README.md

@@ -83,7 +83,7 @@ cuDF can be installed with conda (via [miniconda](https://docs.conda.io/projects
 
 ```bash
 conda install -c rapidsai -c conda-forge -c nvidia \
-    cudf=24.08 python=3.11 cuda-version=12.2
+    cudf=24.08 python=3.11 cuda-version=12.5
 ```
 
 We also provide [nightly Conda packages](https://anaconda.org/rapidsai-nightly) built from the HEAD

conda/environments/all_cuda-122_arch-x86_64.yaml → conda/environments/all_cuda-125_arch-x86_64.yaml

@@ -23,7 +23,7 @@ dependencies:
 - cuda-nvtx-dev
 - cuda-python>=12.0,<13.0a0
 - cuda-sanitizer-api
-- cuda-version=12.2
+- cuda-version=12.5
 - cupy>=12.0.0
 - cxx-compiler
 - cython>=3.0.3
@@ -96,4 +96,4 @@ dependencies:
 - zlib>=1.2.13
 - pip:
   - git+https://github.com/python-streamz/streamz.git@master
-name: all_cuda-122_arch-x86_64
+name: all_cuda-125_arch-x86_64

conda/recipes/cudf/meta.yaml

@@ -64,6 +64,7 @@ requirements:
     - rapids-build-backend >=0.3.0,<0.4.0.dev0
     - scikit-build-core >=0.7.0
     - dlpack >=0.8,<1.0
+    # TODO: Change to `2.0` for NumPy 2
     - numpy 1.23
     - pyarrow ==16.1.0.*
     - libcudf ={{ version }}
@@ -82,7 +83,8 @@ requirements:
     - pandas >=2.0,<2.2.3dev0
     - cupy >=12.0.0
     - numba >=0.57
-    - {{ pin_compatible('numpy', max_pin='x') }}
+    # TODO: Update `numpy` in `host` when dropping `<2.0a0`
+    - numpy >=1.23,<2.0a0
     - {{ pin_compatible('pyarrow', max_pin='x.x') }}
     - libcudf ={{ version }}
     - {{ pin_compatible('rmm', max_pin='x.x') }}

cpp/CMakeLists.txt

@@ -216,6 +216,8 @@ include(cmake/thirdparty/get_fmt.cmake)
 include(cmake/thirdparty/get_spdlog.cmake)
 # find nanoarrow
 include(cmake/thirdparty/get_nanoarrow.cmake)
+# find thread_pool
+include(cmake/thirdparty/get_thread_pool.cmake)
 
 # Workaround until https://github.com/rapidsai/rapids-cmake/issues/176 is resolved
 if(NOT BUILD_SHARED_LIBS)
@@ -672,6 +674,7 @@ add_library(
   src/utilities/linked_column.cpp
   src/utilities/logger.cpp
   src/utilities/pinned_memory.cpp
+  src/utilities/prefetch.cpp
   src/utilities/stacktrace.cpp
   src/utilities/stream_pool.cpp
   src/utilities/traits.cpp
@@ -804,7 +807,7 @@ add_dependencies(cudf jitify_preprocess_run)
 # Specify the target module library dependencies
 target_link_libraries(
   cudf
-  PUBLIC ${ARROW_LIBRARIES} CCCL::CCCL rmm::rmm
+  PUBLIC ${ARROW_LIBRARIES} CCCL::CCCL rmm::rmm $<BUILD_LOCAL_INTERFACE:BS_thread_pool>
   PRIVATE $<BUILD_LOCAL_INTERFACE:nvtx3::nvtx3-cpp> cuco::cuco ZLIB::ZLIB nvcomp::nvcomp
           kvikio::kvikio $<TARGET_NAME_IF_EXISTS:cuFile_interface> nanoarrow
 )

cpp/benchmarks/copying/gather.cu

@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2019-2023, NVIDIA CORPORATION.
+ * Copyright (c) 2019-2024, NVIDIA CORPORATION.
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -71,5 +71,5 @@ void BM_gather(benchmark::State& state)
     ->Ranges({{1 << 10, 1 << 26}, {1, 8}})                     \
     ->UseManualTime();
 
-GBM_BENCHMARK_DEFINE(double_coalesce_x, double, true);
-GBM_BENCHMARK_DEFINE(double_coalesce_o, double, false);
+GBM_BENCHMARK_DEFINE(double_coalesced, double, true);
+GBM_BENCHMARK_DEFINE(double_shuffled, double, false);

cpp/benchmarks/copying/scatter.cu

@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2019-2023, NVIDIA CORPORATION.
+ * Copyright (c) 2019-2024, NVIDIA CORPORATION.
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -74,5 +74,5 @@ void BM_scatter(benchmark::State& state)
     ->Ranges({{1 << 10, 1 << 25}, {1, 8}})                      \
     ->UseManualTime();
 
-SBM_BENCHMARK_DEFINE(double_coalesce_x, double, true);
-SBM_BENCHMARK_DEFINE(double_coalesce_o, double, false);
+SBM_BENCHMARK_DEFINE(double_coalesced, double, true);
+SBM_BENCHMARK_DEFINE(double_shuffled, double, false);

cpp/benchmarks/groupby/group_max_multithreaded.cpp

@@ -20,8 +20,8 @@
 #include <cudf/detail/utilities/stream_pool.hpp>
 #include <cudf/groupby.hpp>
 #include <cudf/utilities/default_stream.hpp>
-#include <cudf/utilities/thread_pool.hpp>
 
+#include <BS_thread_pool.hpp>
 #include <nvbench/nvbench.cuh>
 
 template <typename Type>
@@ -58,7 +58,7 @@ void bench_groupby_max_multithreaded(nvbench::state& state, nvbench::type_list<T
   auto gb_obj    = cudf::groupby::groupby(cudf::table_view({keys_view, keys_view, keys_view}));
 
   auto streams = cudf::detail::fork_streams(cudf::get_default_stream(), num_threads);
-  cudf::detail::thread_pool threads(num_threads);
+  BS::thread_pool threads(num_threads);
 
   std::vector<std::vector<cudf::groupby::aggregation_request>> requests(num_threads);
   for (auto& thread_requests : requests) {
@@ -75,10 +75,8 @@ void bench_groupby_max_multithreaded(nvbench::state& state, nvbench::type_list<T
     nvbench::exec_tag::sync | nvbench::exec_tag::timer, [&](nvbench::launch& launch, auto& timer) {
       auto perform_agg = [&](int64_t index) { gb_obj.aggregate(requests[index], streams[index]); };
       timer.start();
-      for (int64_t i = 0; i < num_threads; ++i) {
-        threads.submit(perform_agg, i);
-      }
-      threads.wait_for_tasks();
+      threads.detach_sequence(decltype(num_threads){0}, num_threads, perform_agg);
+      threads.wait();
       cudf::detail::join_streams(streams, cudf::get_default_stream());
       cudf::get_default_stream().synchronize();
       timer.stop();

cpp/benchmarks/io/orc/orc_reader_multithreaded.cpp

@@ -24,8 +24,8 @@
 #include <cudf/io/orc.hpp>
 #include <cudf/utilities/default_stream.hpp>
 #include <cudf/utilities/pinned_memory.hpp>
-#include <cudf/utilities/thread_pool.hpp>
 
+#include <BS_thread_pool.hpp>
 #include <nvbench/nvbench.cuh>
 
 #include <vector>
@@ -90,7 +90,7 @@ void BM_orc_multithreaded_read_common(nvbench::state& state,
   auto const num_threads = state.get_int64("num_threads");
 
   auto streams = cudf::detail::fork_streams(cudf::get_default_stream(), num_threads);
-  cudf::detail::thread_pool threads(num_threads);
+  BS::thread_pool threads(num_threads);
 
   auto [source_sink_vector, total_file_size, num_files] = write_file_data(state, d_types);
   std::vector<cudf::io::source_info> source_info_vector;
@@ -112,13 +112,11 @@ void BM_orc_multithreaded_read_common(nvbench::state& state,
                    cudf::io::read_orc(read_opts, stream, rmm::mr::get_current_device_resource());
                  };
 
-                 threads.paused = true;
-                 for (size_t i = 0; i < num_files; ++i) {
-                   threads.submit(read_func, i);
-                 }
+                 threads.pause();
+                 threads.detach_sequence(decltype(num_files){0}, num_files, read_func);
                  timer.start();
-                 threads.paused = false;
-                 threads.wait_for_tasks();
+                 threads.unpause();
+                 threads.wait();
                  cudf::detail::join_streams(streams, cudf::get_default_stream());
                  timer.stop();
                });
@@ -170,7 +168,7 @@ void BM_orc_multithreaded_read_chunked_common(nvbench::state& state,
   size_t const output_limit = state.get_int64("output_limit");
 
   auto streams = cudf::detail::fork_streams(cudf::get_default_stream(), num_threads);
-  cudf::detail::thread_pool threads(num_threads);
+  BS::thread_pool threads(num_threads);
   auto [source_sink_vector, total_file_size, num_files] = write_file_data(state, d_types);
   std::vector<cudf::io::source_info> source_info_vector;
   std::transform(source_sink_vector.begin(),
@@ -203,13 +201,11 @@ void BM_orc_multithreaded_read_chunked_common(nvbench::state& state,
                    } while (reader.has_next());
                  };
 
-                 threads.paused = true;
-                 for (size_t i = 0; i < num_files; ++i) {
-                   threads.submit(read_func, i);
-                 }
+                 threads.pause();
+                 threads.detach_sequence(decltype(num_files){0}, num_files, read_func);
                  timer.start();
-                 threads.paused = false;
-                 threads.wait_for_tasks();
+                 threads.unpause();
+                 threads.wait();
                  cudf::detail::join_streams(streams, cudf::get_default_stream());
                  timer.stop();
                });

cpp/benchmarks/io/parquet/parquet_reader_multithread.cpp

@@ -23,10 +23,10 @@
 #include <cudf/io/parquet.hpp>
 #include <cudf/utilities/default_stream.hpp>
 #include <cudf/utilities/pinned_memory.hpp>
-#include <cudf/utilities/thread_pool.hpp>
 
 #include <nvtx3/nvtx3.hpp>
 
+#include <BS_thread_pool.hpp>
 #include <nvbench/nvbench.cuh>
 
 #include <vector>
@@ -93,7 +93,7 @@ void BM_parquet_multithreaded_read_common(nvbench::state& state,
   auto const num_threads = state.get_int64("num_threads");
 
   auto streams = cudf::detail::fork_streams(cudf::get_default_stream(), num_threads);
-  cudf::detail::thread_pool threads(num_threads);
+  BS::thread_pool threads(num_threads);
 
   auto [source_sink_vector, total_file_size, num_files] = write_file_data(state, d_types);
   std::vector<cudf::io::source_info> source_info_vector;
@@ -114,13 +114,11 @@ void BM_parquet_multithreaded_read_common(nvbench::state& state,
                  cudf::io::read_parquet(read_opts, stream, rmm::mr::get_current_device_resource());
                };
 
-               threads.paused = true;
-               for (size_t i = 0; i < num_files; ++i) {
-                 threads.submit(read_func, i);
-               }
+               threads.pause();
+               threads.detach_sequence(decltype(num_files){0}, num_files, read_func);
                timer.start();
-               threads.paused = false;
-               threads.wait_for_tasks();
+               threads.unpause();
+               threads.wait();
                cudf::detail::join_streams(streams, cudf::get_default_stream());
                timer.stop();
              });
@@ -176,7 +174,7 @@ void BM_parquet_multithreaded_read_chunked_common(nvbench::state& state,
   size_t const output_limit = state.get_int64("output_limit");
 
   auto streams = cudf::detail::fork_streams(cudf::get_default_stream(), num_threads);
-  cudf::detail::thread_pool threads(num_threads);
+  BS::thread_pool threads(num_threads);
   auto [source_sink_vector, total_file_size, num_files] = write_file_data(state, d_types);
   std::vector<cudf::io::source_info> source_info_vector;
   std::transform(source_sink_vector.begin(),
@@ -207,13 +205,11 @@ void BM_parquet_multithreaded_read_chunked_common(nvbench::state& state,
                  } while (reader.has_next());
                };
 
-               threads.paused = true;
-               for (size_t i = 0; i < num_files; ++i) {
-                 threads.submit(read_func, i);
-               }
+               threads.pause();
+               threads.detach_sequence(decltype(num_files){0}, num_files, read_func);
                timer.start();
-               threads.paused = false;
-               threads.wait_for_tasks();
+               threads.unpause();
+               threads.wait();
                cudf::detail::join_streams(streams, cudf::get_default_stream());
                timer.stop();
              });

cpp/benchmarks/lists/copying/scatter_lists.cu

@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2021-2023, NVIDIA CORPORATION.
+ * Copyright (c) 2021-2024, NVIDIA CORPORATION.
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -143,5 +143,5 @@ void BM_lists_scatter(::benchmark::State& state)
     ->Ranges({{1 << 10, 1 << 25}, {64, 2048}}) /* 1K-1B rows, 64-2048 elements */ \
     ->UseManualTime();
 
-SBM_BENCHMARK_DEFINE(double_type_colesce_o, double, true);
-SBM_BENCHMARK_DEFINE(double_type_colesce_x, double, false);
+SBM_BENCHMARK_DEFINE(double_coalesced, double, true);
+SBM_BENCHMARK_DEFINE(double_shuffled, double, false);

cpp/benchmarks/text/jaccard.cpp

@@ -59,6 +59,6 @@ static void bench_jaccard(nvbench::state& state)
 
 NVBENCH_BENCH(bench_jaccard)
   .set_name("jaccard")
-  .add_int64_axis("num_rows", {1024, 4096, 8192, 16364, 32768, 262144})
-  .add_int64_axis("row_width", {128, 512, 2048})
+  .add_int64_axis("num_rows", {32768, 131072, 262144})
+  .add_int64_axis("row_width", {128, 512, 1024, 2048})
   .add_int64_axis("substring_width", {5, 10});