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
83 lines
2.2 KiB
Plaintext
83 lines
2.2 KiB
Plaintext
#include <thrust/execution_policy.h>
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#include <thrust/functional.h>
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#include <thrust/partition.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 Iterator1, typename Predicate, typename Iterator2>
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__global__ void
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partition_point_kernel(ExecutionPolicy exec, Iterator1 first, Iterator1 last, Predicate pred, Iterator2 result)
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{
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*result = thrust::partition_point(exec, first, last, pred);
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}
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template <typename T>
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struct is_even
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{
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_CCCL_HOST_DEVICE bool operator()(T x) const
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{
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return ((int) x % 2) == 0;
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}
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};
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template <typename ExecutionPolicy>
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void TestPartitionPointDevice(ExecutionPolicy exec)
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{
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size_t n = 1000;
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thrust::device_vector<int> v = unittest::random_integers<int>(n);
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using iterator = typename thrust::device_vector<int>::iterator;
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iterator ref = thrust::stable_partition(v.begin(), v.end(), is_even<int>());
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thrust::device_vector<iterator> result(1);
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partition_point_kernel<<<1, 1>>>(exec, v.begin(), v.end(), is_even<int>(), 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(ref - v.begin(), (iterator) result[0] - v.begin());
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}
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void TestPartitionPointDeviceSeq()
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{
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TestPartitionPointDevice(thrust::seq);
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}
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DECLARE_UNITTEST(TestPartitionPointDeviceSeq);
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void TestPartitionPointDeviceDevice()
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{
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TestPartitionPointDevice(thrust::device);
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}
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DECLARE_UNITTEST(TestPartitionPointDeviceDevice);
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#endif
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void TestPartitionPointCudaStreams()
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{
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using Vector = thrust::device_vector<int>;
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using T = Vector::value_type;
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using Iterator = Vector::iterator;
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Vector v(4);
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v[0] = 1;
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v[1] = 1;
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v[2] = 1;
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v[3] = 0;
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Iterator first = v.begin();
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Iterator last = v.begin() + 4;
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Iterator ref = first + 3;
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cudaStream_t s;
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cudaStreamCreate(&s);
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ASSERT_EQUAL_QUIET(ref, thrust::partition_point(thrust::cuda::par.on(s), first, last, ::cuda::std::identity{}));
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last = v.begin() + 3;
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ref = last;
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ASSERT_EQUAL_QUIET(ref, thrust::partition_point(thrust::cuda::par.on(s), first, last, ::cuda::std::identity{}));
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cudaStreamDestroy(s);
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}
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DECLARE_UNITTEST(TestPartitionPointCudaStreams);
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