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
104 lines
3.0 KiB
Plaintext
104 lines
3.0 KiB
Plaintext
#include <thrust/count.h>
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#include <thrust/execution_policy.h>
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#include <unittest/unittest.h>
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#ifdef THRUST_TEST_DEVICE_SIDE
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template <typename ExecutionPolicy, typename Iterator, typename T, typename Iterator2>
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__global__ void count_kernel(ExecutionPolicy exec, Iterator first, Iterator last, T value, Iterator2 result)
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{
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*result = thrust::count(exec, first, last, value);
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}
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template <typename T, typename ExecutionPolicy>
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void TestCountDevice(ExecutionPolicy exec, const size_t n)
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{
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thrust::host_vector<T> h_data = unittest::random_samples<T>(n);
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thrust::device_vector<T> d_data = h_data;
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thrust::device_vector<size_t> d_result(1);
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size_t h_result = thrust::count(h_data.begin(), h_data.end(), T(5));
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count_kernel<<<1, 1>>>(exec, d_data.begin(), d_data.end(), T(5), d_result.begin());
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cudaError_t const err = cudaDeviceSynchronize();
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ASSERT_EQUAL(cudaSuccess, err);
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ASSERT_EQUAL(h_result, d_result[0]);
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}
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template <typename T>
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void TestCountDeviceSeq(const size_t n)
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{
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TestCountDevice<T>(thrust::seq, n);
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}
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DECLARE_VARIABLE_UNITTEST(TestCountDeviceSeq);
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template <typename T>
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void TestCountDeviceDevice(const size_t n)
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{
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TestCountDevice<T>(thrust::device, n);
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}
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DECLARE_VARIABLE_UNITTEST(TestCountDeviceDevice);
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template <typename ExecutionPolicy, typename Iterator, typename Predicate, typename Iterator2>
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__global__ void count_if_kernel(ExecutionPolicy exec, Iterator first, Iterator last, Predicate pred, Iterator2 result)
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{
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*result = thrust::count_if(exec, first, last, pred);
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}
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template <typename T>
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struct greater_than_five
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{
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_CCCL_HOST_DEVICE bool operator()(const T& x) const
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{
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return x > 5;
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}
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};
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template <typename T, typename ExecutionPolicy>
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void TestCountIfDevice(ExecutionPolicy exec, const size_t n)
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{
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thrust::host_vector<T> h_data = unittest::random_samples<T>(n);
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thrust::device_vector<T> d_data = h_data;
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thrust::device_vector<size_t> d_result(1);
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size_t h_result = thrust::count_if(h_data.begin(), h_data.end(), greater_than_five<T>());
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count_if_kernel<<<1, 1>>>(exec, d_data.begin(), d_data.end(), greater_than_five<T>(), d_result.begin());
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cudaError_t const err = cudaDeviceSynchronize();
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ASSERT_EQUAL(cudaSuccess, err);
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ASSERT_EQUAL(h_result, d_result[0]);
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}
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template <typename T>
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void TestCountIfDeviceSeq(const size_t n)
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{
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TestCountIfDevice<T>(thrust::seq, n);
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}
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DECLARE_VARIABLE_UNITTEST(TestCountIfDeviceSeq);
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template <typename T>
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void TestCountIfDeviceDevice(const size_t n)
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{
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TestCountIfDevice<T>(thrust::device, n);
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}
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DECLARE_VARIABLE_UNITTEST(TestCountIfDeviceDevice);
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#endif
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void TestCountCudaStreams()
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{
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thrust::device_vector<int> data{1, 1, 0, 0, 1};
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cudaStream_t s;
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cudaStreamCreate(&s);
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ASSERT_EQUAL(thrust::count(thrust::cuda::par.on(s), data.begin(), data.end(), 0), 2);
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ASSERT_EQUAL(thrust::count(thrust::cuda::par.on(s), data.begin(), data.end(), 1), 3);
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ASSERT_EQUAL(thrust::count(thrust::cuda::par.on(s), data.begin(), data.end(), 2), 0);
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cudaStreamDestroy(s);
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}
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DECLARE_UNITTEST(TestCountCudaStreams);
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