56fd68e7dd
CCCL (CUDA C++ Core Libraries) provides: - CUB: device/block/warp-level GPU primitives (reduce, scan, sort, topk) - Thrust: high-level parallel algorithms (transform_reduce, sort, scan) - libcudacxx: CUDA C++ standard library (atomics, barriers, memory) - cudax: experimental features (memory resources, allocators) - Tuning policies: per-SM hardware-specific algorithm parameters Competition optimization vectors mapped to CCCL: - Output TPS (83% weight): warp_reduce, block_reduce, device_topk - Input TPS (14% weight): device_scan, block_load, prefetch - Cache TPS (3% weight): prefix caching strategy patterns - Memory (0.9 util): pooled/cached/buddy allocators Source: https://github.com/NVIDIA/cccl (shallow clone, HEAD only) License: Apache-2.0
75 lines
2.6 KiB
Plaintext
75 lines
2.6 KiB
Plaintext
#include <thrust/scan.h>
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#include <thrust/transform.h>
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#include <cuda/std/utility>
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#include <unittest/unittest.h>
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#if THRUST_DEVICE_SYSTEM == THRUST_DEVICE_SYSTEM_CUDA
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# include <unittest/cuda/testframework.h>
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#endif
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struct make_pair_functor
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{
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template <typename T1, typename T2>
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_CCCL_HOST_DEVICE cuda::std::pair<T1, T2> operator()(const T1& x, const T2& y)
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{
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return cuda::std::make_pair(x, y);
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} // end operator()()
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}; // end make_pair_functor
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struct add_pairs
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{
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template <typename Pair1, typename Pair2>
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_CCCL_HOST_DEVICE Pair1 operator()(const Pair1& x, const Pair2& y)
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{
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return cuda::std::make_pair(x.first + y.first, x.second + y.second);
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} // end operator()
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}; // end add_pairs
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template <typename T>
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struct TestPairScan
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{
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void operator()(const size_t n)
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{
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using P = cuda::std::pair<T, T>;
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thrust::host_vector<T> h_p1 = unittest::random_integers<T>(n);
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thrust::host_vector<T> h_p2 = unittest::random_integers<T>(n);
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thrust::host_vector<P> h_pairs(n);
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thrust::host_vector<P> h_output(n);
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// zip up pairs on the host
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thrust::transform(h_p1.begin(), h_p1.end(), h_p2.begin(), h_pairs.begin(), make_pair_functor());
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thrust::device_vector<T> d_p1 = h_p1;
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thrust::device_vector<T> d_p2 = h_p2;
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thrust::device_vector<P> d_pairs = h_pairs;
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thrust::device_vector<P> d_output(n);
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P init = cuda::std::make_pair(13, 13);
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// scan with plus
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thrust::inclusive_scan(h_pairs.begin(), h_pairs.end(), h_output.begin(), add_pairs());
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thrust::inclusive_scan(d_pairs.begin(), d_pairs.end(), d_output.begin(), add_pairs());
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ASSERT_EQUAL_QUIET(h_output, d_output);
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// scan with maximum (thrust issue #69)
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thrust::inclusive_scan(h_pairs.begin(), h_pairs.end(), h_output.begin(), ::cuda::maximum<P>());
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thrust::inclusive_scan(d_pairs.begin(), d_pairs.end(), d_output.begin(), ::cuda::maximum<P>());
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ASSERT_EQUAL_QUIET(h_output, d_output);
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// scan with plus
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thrust::exclusive_scan(h_pairs.begin(), h_pairs.end(), h_output.begin(), init, add_pairs());
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thrust::exclusive_scan(d_pairs.begin(), d_pairs.end(), d_output.begin(), init, add_pairs());
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ASSERT_EQUAL_QUIET(h_output, d_output);
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// scan with maximum (thrust issue #69)
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thrust::exclusive_scan(h_pairs.begin(), h_pairs.end(), h_output.begin(), init, ::cuda::maximum<P>());
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thrust::exclusive_scan(d_pairs.begin(), d_pairs.end(), d_output.begin(), init, ::cuda::maximum<P>());
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ASSERT_EQUAL_QUIET(h_output, d_output);
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}
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};
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VariableUnitTest<TestPairScan, unittest::type_list<unittest::int8_t, unittest::int16_t, unittest::int32_t>>
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TestPairScanInstance;
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