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
129 lines
3.2 KiB
Plaintext
129 lines
3.2 KiB
Plaintext
#include <thrust/functional.h>
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#include <thrust/iterator/retag.h>
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#include <thrust/sort.h>
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#include <unittest/unittest.h>
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template <typename RandomAccessIterator>
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void sort(my_system& system, RandomAccessIterator, RandomAccessIterator)
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{
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system.validate_dispatch();
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}
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void TestSortDispatchExplicit()
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{
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thrust::device_vector<int> vec(1);
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my_system sys(0);
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thrust::sort(sys, vec.begin(), vec.begin());
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ASSERT_EQUAL(true, sys.is_valid());
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}
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DECLARE_UNITTEST(TestSortDispatchExplicit);
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template <typename RandomAccessIterator>
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void sort(my_tag, RandomAccessIterator first, RandomAccessIterator)
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{
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*first = 13;
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}
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void TestSortDispatchImplicit()
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{
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thrust::device_vector<int> vec(1);
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thrust::sort(thrust::retag<my_tag>(vec.begin()), thrust::retag<my_tag>(vec.begin()));
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ASSERT_EQUAL(13, vec.front());
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}
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DECLARE_UNITTEST(TestSortDispatchImplicit);
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template <class Vector>
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void InitializeSimpleKeySortTest(Vector& unsorted_keys, Vector& sorted_keys)
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{
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unsorted_keys.resize(7);
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unsorted_keys = {1, 3, 6, 5, 2, 0, 4};
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sorted_keys.resize(7);
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sorted_keys = {0, 1, 2, 3, 4, 5, 6};
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}
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template <class Vector>
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void TestSortSimple()
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{
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Vector unsorted_keys;
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Vector sorted_keys;
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InitializeSimpleKeySortTest(unsorted_keys, sorted_keys);
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thrust::sort(unsorted_keys.begin(), unsorted_keys.end());
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ASSERT_EQUAL(unsorted_keys, sorted_keys);
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}
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DECLARE_VECTOR_UNITTEST(TestSortSimple);
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template <typename T>
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void TestSortAscendingKey(const size_t n)
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{
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thrust::host_vector<T> h_data = unittest::random_integers<T>(n);
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thrust::device_vector<T> d_data = h_data;
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thrust::sort(h_data.begin(), h_data.end(), ::cuda::std::less<T>());
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thrust::sort(d_data.begin(), d_data.end(), ::cuda::std::less<T>());
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ASSERT_EQUAL(h_data, d_data);
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}
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DECLARE_VARIABLE_UNITTEST(TestSortAscendingKey);
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void TestSortDescendingKey()
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{
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const size_t n = 10027;
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thrust::host_vector<int> h_data = unittest::random_integers<int>(n);
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thrust::device_vector<int> d_data = h_data;
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thrust::sort(h_data.begin(), h_data.end(), ::cuda::std::greater<int>());
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thrust::sort(d_data.begin(), d_data.end(), ::cuda::std::greater<int>());
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ASSERT_EQUAL(h_data, d_data);
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}
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DECLARE_UNITTEST(TestSortDescendingKey);
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void TestSortBool()
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{
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const size_t n = 10027;
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thrust::host_vector<bool> h_data = unittest::random_integers<bool>(n);
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thrust::device_vector<bool> d_data = h_data;
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thrust::sort(h_data.begin(), h_data.end());
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thrust::sort(d_data.begin(), d_data.end());
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ASSERT_EQUAL(h_data, d_data);
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}
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DECLARE_UNITTEST(TestSortBool);
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void TestSortBoolDescending()
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{
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const size_t n = 10027;
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thrust::host_vector<bool> h_data = unittest::random_integers<bool>(n);
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thrust::device_vector<bool> d_data = h_data;
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thrust::sort(h_data.begin(), h_data.end(), ::cuda::std::greater<bool>());
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thrust::sort(d_data.begin(), d_data.end(), ::cuda::std::greater<bool>());
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ASSERT_EQUAL(h_data, d_data);
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}
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DECLARE_UNITTEST(TestSortBoolDescending);
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// See also: https://github.com/NVIDIA/cccl/issues/4919
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void TestSortTrivial()
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{
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thrust::host_vector<int> h_data = {1, 0, -1, -2, -3};
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thrust::host_vector<int> ref = {-3, -2, -1, 0, 1};
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thrust::sort(h_data.begin(), h_data.end());
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ASSERT_EQUAL(h_data, ref);
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}
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DECLARE_UNITTEST(TestSortTrivial);
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