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
59 lines
1.8 KiB
Plaintext
59 lines
1.8 KiB
Plaintext
#include <thrust/reduce.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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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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// Need cast to undo integer promotion, decltype(char{} + char{}) == int
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using P1T1 = typename Pair1::first_type;
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using P1T2 = typename Pair1::second_type;
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return cuda::std::make_pair(static_cast<P1T1>(x.first + y.first), static_cast<P1T2>(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 TestPairReduce
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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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// 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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P init = cuda::std::make_pair(T{13}, T{13});
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// reduce on the host
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P h_result = thrust::reduce(h_pairs.begin(), h_pairs.end(), init, add_pairs());
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// reduce on the device
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P d_result = thrust::reduce(d_pairs.begin(), d_pairs.end(), init, add_pairs());
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ASSERT_EQUAL_QUIET(h_result, d_result);
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}
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}; // end TestPairReduce
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VariableUnitTest<TestPairReduce, SignedIntegralTypes> TestPairReduceInstance;
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