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move benchmark input generation in device in reduction nvbench #10486

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merged 1 commit into from
Mar 28, 2022
+10 −12
Merged

move benchmark input generation in device in reduction nvbench #10486

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22 changes: 10 additions & 12 deletions cpp/benchmarks/reduction/segment_reduce.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -14,12 +14,10 @@
* limitations under the License.
*/

#include <benchmarks/common/generate_input.hpp>
#include <benchmarks/fixture/rmm_pool_raii.hpp>
#include <nvbench/nvbench.cuh>

#include <cudf_test/base_fixture.hpp>
#include <cudf_test/column_wrapper.hpp>

#include <cudf/aggregation.hpp>
#include <cudf/column/column.hpp>
#include <cudf/detail/iterator.cuh>
Expand All @@ -33,7 +31,6 @@

#include <memory>
#include <type_traits>
#include <vector>

namespace cudf {

Expand Down Expand Up @@ -71,20 +68,21 @@ std::pair<std::unique_ptr<column>, thrust::device_vector<size_type>> make_test_d

auto segment_length = column_size / num_segments;

test::UniformRandomGenerator<InputType> rand_gen(0, 100);
auto data_it = detail::make_counting_transform_iterator(
0, [&rand_gen](auto i) { return rand_gen.generate(); });
auto const dtype = cudf::type_to_id<InputType>();
data_profile profile;
profile.set_null_frequency(std::nullopt);
profile.set_cardinality(0);
profile.set_distribution_params(dtype, distribution_id::UNIFORM, 0, 100);
auto input = create_random_table({dtype}, row_count{column_size}, profile);

auto offset_it =
detail::make_counting_transform_iterator(0, [&column_size, &segment_length](auto i) {
detail::make_counting_transform_iterator(0, [column_size, segment_length] __device__(auto i) {
return column_size < i * segment_length ? column_size : i * segment_length;
});

test::fixed_width_column_wrapper<InputType> input(data_it, data_it + column_size);
std::vector<size_type> h_offsets(offset_it, offset_it + num_segments + 1);
thrust::device_vector<size_type> d_offsets(h_offsets);
thrust::device_vector<size_type> d_offsets(offset_it, offset_it + num_segments + 1);

return std::make_pair(input.release(), d_offsets);
return std::make_pair(std::move((input->release())[0]), d_offsets);
}

template <typename InputType, typename OutputType, aggregation::Kind kind>
Expand Down