Merge branch 'branch-24.06' into custom-rapids-cmake

ci/build_docs.sh

@@ -11,7 +11,7 @@ rapids-dependency-file-generator \
   --file_key docs \
   --matrix "cuda=${RAPIDS_CUDA_VERSION%.*};arch=$(arch);py=${RAPIDS_PY_VERSION}" | tee env.yaml
 
-rapids-mamba-retry env create --force -f env.yaml -n docs
+rapids-mamba-retry env create --yes -f env.yaml -n docs
 conda activate docs
 
 rapids-print-env

ci/check_style.sh

@@ -1,5 +1,5 @@
 #!/bin/bash
-# Copyright (c) 2020-2023, NVIDIA CORPORATION.
+# Copyright (c) 2020-2024, NVIDIA CORPORATION.
 
 set -euo pipefail
 
@@ -11,7 +11,7 @@ rapids-dependency-file-generator \
   --file_key checks \
   --matrix "cuda=${RAPIDS_CUDA_VERSION%.*};arch=$(arch);py=${RAPIDS_PY_VERSION}" | tee env.yaml
 
-rapids-mamba-retry env create --force -f env.yaml -n checks
+rapids-mamba-retry env create --yes -f env.yaml -n checks
 conda activate checks
 
 # Run pre-commit checks

ci/test_cpp.sh

@@ -14,7 +14,7 @@ rapids-dependency-file-generator \
   --file_key test_cpp \
   --matrix "cuda=${RAPIDS_CUDA_VERSION%.*};arch=$(arch)" | tee env.yaml
 
-rapids-mamba-retry env create --force -f env.yaml -n test
+rapids-mamba-retry env create --yes -f env.yaml -n test
 
 # Temporarily allow unbound variables for conda activation.
 set +u

ci/test_python.sh

@@ -14,7 +14,7 @@ rapids-dependency-file-generator \
   --file_key test_python \
   --matrix "cuda=${RAPIDS_CUDA_VERSION%.*};arch=$(arch);py=${RAPIDS_PY_VERSION}" | tee env.yaml
 
-rapids-mamba-retry env create --force -f env.yaml -n test
+rapids-mamba-retry env create --yes -f env.yaml -n test
 
 # Temporarily allow unbound variables for conda activation.
 set +u

cpp/bench/prims/CMakeLists.txt

@@ -137,6 +137,7 @@ if(BUILD_PRIMS_BENCH)
     PATH
     bench/prims/sparse/bitmap_to_csr.cu
     bench/prims/sparse/convert_csr.cu
+    bench/prims/sparse/select_k_csr.cu
     bench/prims/main.cpp
   )
 

cpp/bench/prims/sparse/select_k_csr.cu

@@ -0,0 +1,287 @@
+/*
+ * Copyright (c) 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.
+ * 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/core/device_csr_matrix.hpp>
+#include <raft/core/device_mdarray.hpp>
+#include <raft/core/device_mdspan.hpp>
+#include <raft/core/device_resources.hpp>
+#include <raft/core/resource/cuda_stream.hpp>
+#include <raft/core/resources.hpp>
+#include <raft/matrix/copy.cuh>
+#include <raft/random/make_blobs.cuh>
+#include <raft/random/rng_state.hpp>
+#include <raft/sparse/convert/csr.cuh>
+#include <raft/sparse/matrix/select_k.cuh>
+#include <raft/util/cuda_utils.cuh>
+#include <raft/util/itertools.hpp>
+
+#include <rmm/device_uvector.hpp>
+
+#include <random>
+#include <sstream>
+#include <unordered_set>
+#include <vector>
+
+namespace raft::bench::sparse {
+
+template <typename index_t>
+struct bench_param {
+  index_t n_rows;
+  index_t n_cols;
+  index_t top_k;
+  float sparsity;
+  bool select_min         = true;
+  bool customized_indices = false;
+};
+
+template <typename index_t>
+inline auto operator<<(std::ostream& os, const bench_param<index_t>& params) -> std::ostream&
+{
+  os << params.n_rows << "#" << params.n_cols << "#" << params.top_k << "#" << params.sparsity;
+  return os;
+}
+
+template <typename value_t, typename index_t>
+struct SelectKCsrTest : public fixture {
+  SelectKCsrTest(const bench_param<index_t>& p)
+    : fixture(true),
+      params(p),
+      handle(stream),
+      values_d(0, stream),
+      indptr_d(0, stream),
+      indices_d(0, stream),
+      customized_indices_d(0, stream),
+      dst_values_d(0, stream),
+      dst_indices_d(0, stream)
+  {
+    std::vector<bool> dense_values_h(params.n_rows * params.n_cols);
+    nnz = create_sparse_matrix(params.n_rows, params.n_cols, params.sparsity, dense_values_h);
+
+    std::vector<index_t> indices_h(nnz);
+    std::vector<index_t> customized_indices_h(nnz);
+    std::vector<index_t> indptr_h(params.n_rows + 1);
+
+    convert_to_csr(dense_values_h, params.n_rows, params.n_cols, indices_h, indptr_h);
+
+    std::vector<value_t> dst_values_h(params.n_rows * params.top_k, static_cast<value_t>(2.0f));
+    std::vector<index_t> dst_indices_h(params.n_rows * params.top_k,
+                                       static_cast<index_t>(params.n_rows * params.n_cols * 100));
+
+    dst_values_d.resize(params.n_rows * params.top_k, stream);
+    dst_indices_d.resize(params.n_rows * params.top_k, stream);
+    values_d.resize(nnz, stream);
+
+    if (nnz) {
+      auto blobs_values = raft::make_device_matrix<value_t, index_t>(handle, 1, nnz);
+      auto labels       = raft::make_device_vector<index_t, index_t>(handle, 1);
+
+      raft::random::make_blobs<value_t, index_t>(blobs_values.data_handle(),
+                                                 labels.data_handle(),
+                                                 1,
+                                                 nnz,
+                                                 1,
+                                                 stream,
+                                                 false,
+                                                 nullptr,
+                                                 nullptr,
+                                                 value_t(1.0),
+                                                 false,
+                                                 value_t(-10.0f),
+                                                 value_t(10.0f),
+                                                 uint64_t(2024));
+      raft::copy(values_d.data(), blobs_values.data_handle(), nnz, stream);
+      resource::sync_stream(handle);
+    }
+
+    indices_d.resize(nnz, stream);
+    indptr_d.resize(params.n_rows + 1, stream);
+
+    update_device(indices_d.data(), indices_h.data(), indices_h.size(), stream);
+    update_device(indptr_d.data(), indptr_h.data(), indptr_h.size(), stream);
+
+    if (params.customized_indices) {
+      customized_indices_d.resize(nnz, stream);
+      update_device(customized_indices_d.data(),
+                    customized_indices_h.data(),
+                    customized_indices_h.size(),
+                    stream);
+    }
+  }
+
+  index_t create_sparse_matrix(index_t m, index_t n, value_t sparsity, std::vector<bool>& matrix)
+  {
+    index_t total_elements = static_cast<index_t>(m * n);
+    index_t num_ones       = static_cast<index_t>((total_elements * 1.0f) * sparsity);
+    index_t res            = num_ones;
+
+    for (index_t i = 0; i < total_elements; ++i) {
+      matrix[i] = false;
+    }
+
+    std::random_device rd;
+    std::mt19937 gen(rd());
+    std::uniform_int_distribution<> dis_idx(0, total_elements - 1);
+
+    while (num_ones > 0) {
+      size_t index = dis_idx(gen);
+      if (matrix[index] == false) {
+        matrix[index] = true;
+        num_ones--;
+      }
+    }
+    return res;
+  }
+
+  void convert_to_csr(std::vector<bool>& matrix,
+                      index_t rows,
+                      index_t cols,
+                      std::vector<index_t>& indices,
+                      std::vector<index_t>& indptr)
+  {
+    index_t offset_indptr   = 0;
+    index_t offset_values   = 0;
+    indptr[offset_indptr++] = 0;
+
+    for (index_t i = 0; i < rows; ++i) {
+      for (index_t j = 0; j < cols; ++j) {
+        if (matrix[i * cols + j]) {
+          indices[offset_values] = static_cast<index_t>(j);
+          offset_values++;
+        }
+      }
+      indptr[offset_indptr++] = static_cast<index_t>(offset_values);
+    }
+  }
+
+  template <typename data_t>
+  std::optional<data_t> get_opt_var(data_t x)
+  {
+    if (params.customized_indices) {
+      return x;
+    } else {
+      return std::nullopt;
+    }
+  }
+
+  void run_benchmark(::benchmark::State& state) override
+  {
+    std::ostringstream label_stream;
+    label_stream << params;
+    state.SetLabel(label_stream.str());
+
+    auto in_val_structure = raft::make_device_compressed_structure_view<index_t, index_t, index_t>(
+      indptr_d.data(),
+      indices_d.data(),
+      params.n_rows,
+      params.n_cols,
+      static_cast<index_t>(indices_d.size()));
+
+    auto in_val =
+      raft::make_device_csr_matrix_view<const value_t>(values_d.data(), in_val_structure);
+
+    std::optional<raft::device_vector_view<const index_t, index_t>> in_idx;
+
+    in_idx = get_opt_var(
+      raft::make_device_vector_view<const index_t, index_t>(customized_indices_d.data(), nnz));
+
+    auto out_val = raft::make_device_matrix_view<value_t, index_t, raft::row_major>(
+      dst_values_d.data(), params.n_rows, params.top_k);
+    auto out_idx = raft::make_device_matrix_view<index_t, index_t, raft::row_major>(
+      dst_indices_d.data(), params.n_rows, params.top_k);
+
+    raft::sparse::matrix::select_k(handle, in_val, in_idx, out_val, out_idx, params.select_min);
+    resource::sync_stream(handle);
+    loop_on_state(state, [this, &in_val, &in_idx, &out_val, &out_idx]() {
+      raft::sparse::matrix::select_k(
+        handle, in_val, in_idx, out_val, out_idx, params.select_min, false);
+      resource::sync_stream(handle);
+    });
+  }
+
+ protected:
+  const raft::device_resources handle;
+
+  bench_param<index_t> params;
+  index_t nnz;
+
+  rmm::device_uvector<value_t> values_d;
+  rmm::device_uvector<index_t> indptr_d;
+  rmm::device_uvector<index_t> indices_d;
+  rmm::device_uvector<index_t> customized_indices_d;
+
+  rmm::device_uvector<value_t> dst_values_d;
+  rmm::device_uvector<index_t> dst_indices_d;
+};  // struct SelectKCsrTest
+
+template <typename index_t>
+const std::vector<bench_param<index_t>> getInputs()
+{
+  std::vector<bench_param<index_t>> param_vec;
+  struct TestParams {
+    index_t m;
+    index_t n;
+    index_t k;
+  };
+
+  const std::vector<TestParams> params_group{
+    {20000, 500, 1},    {20000, 500, 2},    {20000, 500, 4},   {20000, 500, 8},
+    {20000, 500, 16},   {20000, 500, 32},   {20000, 500, 64},  {20000, 500, 128},
+    {20000, 500, 256},
+
+    {1000, 10000, 1},   {1000, 10000, 2},   {1000, 10000, 4},  {1000, 10000, 8},
+    {1000, 10000, 16},  {1000, 10000, 32},  {1000, 10000, 64}, {1000, 10000, 128},
+    {1000, 10000, 256},
+
+    {100, 100000, 1},   {100, 100000, 2},   {100, 100000, 4},  {100, 100000, 8},
+    {100, 100000, 16},  {100, 100000, 32},  {100, 100000, 64}, {100, 100000, 128},
+    {100, 100000, 256},
+
+    {10, 1000000, 1},   {10, 1000000, 2},   {10, 1000000, 4},  {10, 1000000, 8},
+    {10, 1000000, 16},  {10, 1000000, 32},  {10, 1000000, 64}, {10, 1000000, 128},
+    {10, 1000000, 256},
+
+    {10, 1000000, 1},   {10, 1000000, 2},   {10, 1000000, 4},  {10, 1000000, 8},
+    {10, 1000000, 16},  {10, 1000000, 32},  {10, 1000000, 64}, {10, 1000000, 128},
+    {10, 1000000, 256},
+
+    {10, 1000000, 1},   {10, 1000000, 16},  {10, 1000000, 64}, {10, 1000000, 128},
+    {10, 1000000, 256},
+
+    {10, 1000000, 1},   {10, 1000000, 16},  {10, 1000000, 64}, {10, 1000000, 128},
+    {10, 1000000, 256}, {1000, 10000, 1},   {1000, 10000, 16}, {1000, 10000, 64},
+    {1000, 10000, 128}, {1000, 10000, 256},
+
+    {10, 1000000, 1},   {10, 1000000, 16},  {10, 1000000, 64}, {10, 1000000, 128},
+    {10, 1000000, 256}, {1000, 10000, 1},   {1000, 10000, 16}, {1000, 10000, 64},
+    {1000, 10000, 128}, {1000, 10000, 256}};
+
+  param_vec.reserve(params_group.size());
+  for (TestParams params : params_group) {
+    param_vec.push_back(bench_param<index_t>({params.m, params.n, params.k, 0.1}));
+  }
+  for (TestParams params : params_group) {
+    param_vec.push_back(bench_param<index_t>({params.m, params.n, params.k, 0.2}));
+  }
+  for (TestParams params : params_group) {
+    param_vec.push_back(bench_param<index_t>({params.m, params.n, params.k, 0.5}));
+  }
+  return param_vec;
+}
+
+RAFT_BENCH_REGISTER((SelectKCsrTest<float, uint32_t>), "", getInputs<uint32_t>());
+
+}  // namespace raft::bench::sparse