Replace dots_along_rows with rowNorm and improve coalescedReduction performance

cpp/bench/CMakeLists.txt

@@ -94,6 +94,7 @@ if(BUILD_BENCH)
     bench/linalg/add.cu
     bench/linalg/map_then_reduce.cu
     bench/linalg/matrix_vector_op.cu
+    bench/linalg/norm.cu
     bench/linalg/reduce_rows_by_key.cu
     bench/linalg/reduce.cu
     bench/main.cpp

cpp/bench/linalg/norm.cu

@@ -0,0 +1,84 @@
+/*
+ * Copyright (c) 2022, NVIDIA CORPORATION.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include <common/benchmark.hpp>
+#include <raft/linalg/matrix_vector_op.cuh>
+#include <raft/linalg/norm.cuh>
+#include <raft/random/rng.cuh>
+#include <raft/util/itertools.hpp>
+
+#include <rmm/device_uvector.hpp>
+
+namespace raft::bench::linalg {
+
+template <typename IdxT>
+struct norm_input {
+  IdxT rows, cols;
+};
+
+template <typename IdxT>
+inline auto operator<<(std::ostream& os, const norm_input<IdxT>& p) -> std::ostream&
+{
+  os << p.rows << "#" << p.cols;
+  return os;
+}
+
+template <typename T, typename IdxT>
+struct rowNorm : public fixture {
+  rowNorm(const norm_input<IdxT>& p) : params(p), in(p.rows * p.cols, stream), dots(p.rows, stream)
+  {
+    raft::random::RngState rng{1234};
+    raft::random::uniform(rng, in.data(), p.rows * p.cols, (T)-10.0, (T)10.0, stream);
+  }
+
+  void run_benchmark(::benchmark::State& state) override
+  {
+    std::ostringstream label_stream;
+    label_stream << params;
+    state.SetLabel(label_stream.str());
+
+    loop_on_state(state, [this]() {
+      auto input_view = raft::make_device_matrix_view<const T, IdxT, raft::row_major>(
+        in.data(), params.rows, params.cols);
+      auto output_view =
+        raft::make_device_vector_view<T, IdxT, raft::row_major>(dots.data(), params.rows);
+      raft::linalg::norm(handle,
+                         input_view,
+                         output_view,
+                         raft::linalg::L2Norm,
+                         raft::linalg::Apply::ALONG_ROWS,
+                         raft::SqrtOp<T>());
+    });
+  }
+
+ private:
+  norm_input<IdxT> params;
+  rmm::device_uvector<T> in, dots;
+};  // struct rowNorm
+
+const std::vector<norm_input<int>> norm_inputs_i32 =
+  raft::util::itertools::product<norm_input<int>>({10, 100, 1000, 10000, 100000},
+                                                  {16, 32, 64, 128, 256, 512, 1024});
+const std::vector<norm_input<int64_t>> norm_inputs_i64 =
+  raft::util::itertools::product<norm_input<int64_t>>({10, 100, 1000, 10000, 100000},
+                                                      {16, 32, 64, 128, 256, 512, 1024});
+
+RAFT_BENCH_REGISTER((rowNorm<float, int>), "", norm_inputs_i32);
+RAFT_BENCH_REGISTER((rowNorm<double, int>), "", norm_inputs_i32);
+RAFT_BENCH_REGISTER((rowNorm<float, int64_t>), "", norm_inputs_i64);
+RAFT_BENCH_REGISTER((rowNorm<double, int64_t>), "", norm_inputs_i64);
+
+}  // namespace raft::bench::linalg

cpp/include/raft/linalg/coalesced_reduction.cuh

@@ -112,21 +112,21 @@ void coalescedReduction(OutType* dots,
 template <typename InValueType,
           typename LayoutPolicy,
           typename OutValueType,
-          typename IndexType,
-          typename MainLambda   = raft::Nop<InValueType>,
+          typename IdxType,
+          typename MainLambda   = raft::Nop<InValueType, IdxType>,
           typename ReduceLambda = raft::Sum<OutValueType>,
           typename FinalLambda  = raft::Nop<OutValueType>>
 void coalesced_reduction(const raft::handle_t& handle,
-                         raft::device_matrix_view<const InValueType, IndexType, LayoutPolicy> data,
-                         raft::device_vector_view<OutValueType, IndexType> dots,
+                         raft::device_matrix_view<const InValueType, IdxType, LayoutPolicy> data,
+                         raft::device_vector_view<OutValueType, IdxType> dots,
                          OutValueType init,
                          bool inplace           = false,
-                         MainLambda main_op     = raft::Nop<InValueType>(),
+                         MainLambda main_op     = raft::Nop<InValueType, IdxType>(),
                          ReduceLambda reduce_op = raft::Sum<OutValueType>(),
                          FinalLambda final_op   = raft::Nop<OutValueType>())
 {
   if constexpr (std::is_same_v<LayoutPolicy, raft::row_major>) {
-    RAFT_EXPECTS(static_cast<IndexType>(dots.size()) == data.extent(0),
+    RAFT_EXPECTS(static_cast<IdxType>(dots.size()) == data.extent(0),
                  "Output should be equal to number of rows in Input");
 
     coalescedReduction(dots.data_handle(),
@@ -140,7 +140,7 @@ void coalesced_reduction(const raft::handle_t& handle,
                        reduce_op,
                        final_op);
   } else if constexpr (std::is_same_v<LayoutPolicy, raft::col_major>) {
-    RAFT_EXPECTS(static_cast<IndexType>(dots.size()) == data.extent(1),
+    RAFT_EXPECTS(static_cast<IdxType>(dots.size()) == data.extent(1),
                  "Output should be equal to number of columns in Input");
 
     coalescedReduction(dots.data_handle(),