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@@ -62,3 +62,33 @@ jobs: | |
| UPDATE_ITEM: true | ||
| UPDATE_LINKED_ISSUES: true | ||
| secrets: inherit | ||
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| process-branch-name: | ||
| if: ${{ github.event.pull_request.state == 'open' && needs.get-project-id.outputs.ITEM_PROJECT_ID != '' }} | ||
| needs: get-project-id | ||
| runs-on: ubuntu-latest | ||
| outputs: | ||
| branch-name: ${{ steps.process-branch-name.outputs.branch-name }} | ||
| steps: | ||
| - name: Extract branch name | ||
| id: process-branch-name | ||
| run: | | ||
| branch=${{ github.event.pull_request.base.ref }} | ||
| release=${branch#branch-} | ||
| echo "branch-name=$release" >> "$GITHUB_OUTPUT" | ||
| update-release: | ||
| # This job sets the PR and its linked issues to the release they are targeting | ||
| uses: rapidsai/shared-workflows/.github/workflows/[email protected] | ||
| if: ${{ github.event.pull_request.state == 'open' && needs.get-project-id.outputs.ITEM_PROJECT_ID != '' }} | ||
| needs: [get-project-id, process-branch-name] | ||
| with: | ||
| PROJECT_ID: "PVT_kwDOAp2shc4AiNzl" | ||
| SINGLE_SELECT_FIELD_ID: "PVTSSF_lADOAp2shc4AiNzlzgg52UQ" | ||
| SINGLE_SELECT_FIELD_NAME: "Release" | ||
| SINGLE_SELECT_OPTION_VALUE: "${{ needs.process-branch-name.outputs.branch-name }}" | ||
| ITEM_PROJECT_ID: "${{ needs.get-project-id.outputs.ITEM_PROJECT_ID }}" | ||
| ITEM_NODE_ID: "${{ github.event.pull_request.node_id }}" | ||
| UPDATE_ITEM: true | ||
| UPDATE_LINKED_ISSUES: true | ||
| secrets: inherit | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,90 @@ | ||
| /* | ||
| * Copyright (c) 2022-2024, 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 <benchmarks/common/generate_input.hpp> | ||
| #include <benchmarks/fixture/benchmark_fixture.hpp> | ||
|
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| #include <cudf/groupby.hpp> | ||
|
|
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| #include <nvbench/nvbench.cuh> | ||
|
|
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| template <typename Type> | ||
| void groupby_histogram_helper(nvbench::state& state, | ||
| cudf::size_type num_rows, | ||
| cudf::size_type cardinality, | ||
| double null_probability) | ||
| { | ||
| auto const keys = [&] { | ||
| data_profile const profile = | ||
| data_profile_builder() | ||
| .cardinality(cardinality) | ||
| .no_validity() | ||
| .distribution(cudf::type_to_id<int32_t>(), distribution_id::UNIFORM, 0, num_rows); | ||
| return create_random_column(cudf::type_to_id<int32_t>(), row_count{num_rows}, profile); | ||
| }(); | ||
|
|
||
| auto const values = [&] { | ||
| auto builder = data_profile_builder().cardinality(0).distribution( | ||
| cudf::type_to_id<Type>(), distribution_id::UNIFORM, 0, num_rows); | ||
| if (null_probability > 0) { | ||
| builder.null_probability(null_probability); | ||
| } else { | ||
| builder.no_validity(); | ||
| } | ||
| return create_random_column( | ||
| cudf::type_to_id<Type>(), row_count{num_rows}, data_profile{builder}); | ||
| }(); | ||
|
|
||
| // Vector of 1 request | ||
| std::vector<cudf::groupby::aggregation_request> requests(1); | ||
| requests.back().values = values->view(); | ||
| requests.back().aggregations.push_back( | ||
| cudf::make_histogram_aggregation<cudf::groupby_aggregation>()); | ||
|
|
||
| auto const mem_stats_logger = cudf::memory_stats_logger(); | ||
| state.set_cuda_stream(nvbench::make_cuda_stream_view(cudf::get_default_stream().value())); | ||
| state.exec(nvbench::exec_tag::sync, [&](nvbench::launch& launch) { | ||
| auto gb_obj = cudf::groupby::groupby(cudf::table_view({keys->view()})); | ||
| auto const result = gb_obj.aggregate(requests); | ||
| }); | ||
|
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| auto const elapsed_time = state.get_summary("nv/cold/time/gpu/mean").get_float64("value"); | ||
| state.add_element_count(static_cast<double>(num_rows) / elapsed_time, "rows/s"); | ||
| state.add_buffer_size( | ||
| mem_stats_logger.peak_memory_usage(), "peak_memory_usage", "peak_memory_usage"); | ||
| } | ||
|
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| template <typename Type> | ||
| void bench_groupby_histogram(nvbench::state& state, nvbench::type_list<Type>) | ||
| { | ||
| auto const cardinality = static_cast<cudf::size_type>(state.get_int64("cardinality")); | ||
| auto const num_rows = static_cast<cudf::size_type>(state.get_int64("num_rows")); | ||
| auto const null_probability = state.get_float64("null_probability"); | ||
|
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| if (cardinality > num_rows) { | ||
| state.skip("cardinality > num_rows"); | ||
| return; | ||
| } | ||
|
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| groupby_histogram_helper<Type>(state, num_rows, cardinality, null_probability); | ||
| } | ||
|
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| NVBENCH_BENCH_TYPES(bench_groupby_histogram, | ||
| NVBENCH_TYPE_AXES(nvbench::type_list<int32_t, int64_t, float, double>)) | ||
| .set_name("groupby_histogram") | ||
| .add_float64_axis("null_probability", {0, 0.1, 0.9}) | ||
| .add_int64_axis("cardinality", {100, 1'000, 10'000, 100'000, 1'000'000, 10'000'000}) | ||
| .add_int64_axis("num_rows", {100, 1'000, 10'000, 100'000, 1'000'000, 10'000'000}); |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,68 @@ | ||
| /* | ||
| * Copyright (c) 2022-2024, 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 "cudf/aggregation.hpp" | ||
| #include "cudf/detail/aggregation/aggregation.hpp" | ||
|
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| #include <benchmarks/common/generate_input.hpp> | ||
| #include <benchmarks/common/nvbench_utilities.hpp> | ||
| #include <benchmarks/common/table_utilities.hpp> | ||
|
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| #include <cudf/column/column_view.hpp> | ||
| #include <cudf/detail/aggregation/aggregation.hpp> | ||
| #include <cudf/reduction.hpp> | ||
| #include <cudf/reduction/detail/histogram.hpp> | ||
| #include <cudf/types.hpp> | ||
|
|
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| #include <nvbench/nvbench.cuh> | ||
|
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| template <typename type> | ||
| static void nvbench_reduction_histogram(nvbench::state& state, nvbench::type_list<type>) | ||
| { | ||
| auto const dtype = cudf::type_to_id<type>(); | ||
|
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| auto const cardinality = static_cast<cudf::size_type>(state.get_int64("cardinality")); | ||
| auto const num_rows = static_cast<cudf::size_type>(state.get_int64("num_rows")); | ||
| auto const null_probability = state.get_float64("null_probability"); | ||
|
|
||
| if (cardinality > num_rows) { | ||
| state.skip("cardinality > num_rows"); | ||
| return; | ||
| } | ||
|
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| data_profile const profile = data_profile_builder() | ||
| .null_probability(null_probability) | ||
| .cardinality(cardinality) | ||
| .distribution(dtype, distribution_id::UNIFORM, 0, num_rows); | ||
|
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| auto const input = create_random_column(dtype, row_count{num_rows}, profile); | ||
| auto agg = cudf::make_histogram_aggregation<cudf::reduce_aggregation>(); | ||
| state.exec(nvbench::exec_tag::sync, [&](nvbench::launch& launch) { | ||
| rmm::cuda_stream_view stream_view{launch.get_stream()}; | ||
| auto result = cudf::reduce(*input, *agg, input->type(), stream_view); | ||
| }); | ||
|
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| state.add_element_count(input->size()); | ||
| } | ||
|
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| using data_type = nvbench::type_list<int32_t, int64_t>; | ||
|
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| NVBENCH_BENCH_TYPES(nvbench_reduction_histogram, NVBENCH_TYPE_AXES(data_type)) | ||
| .set_name("histogram") | ||
| .add_float64_axis("null_probability", {0.1}) | ||
| .add_int64_axis("cardinality", | ||
| {0, 100, 1'000, 10'000, 100'000, 1'000'000, 10'000'000, 50'000'000}) | ||
| .add_int64_axis("num_rows", {10'000, 100'000, 1'000'000, 10'000'000, 100'000'000}); |
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