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
97 lines
2.5 KiB
Plaintext
97 lines
2.5 KiB
Plaintext
#include <thrust/functional.h>
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#include <thrust/iterator/retag.h>
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#include <thrust/partition.h>
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#include <unittest/unittest.h>
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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 Vector>
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void TestIsPartitionedSimple()
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{
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Vector v{1, 1, 1, 0};
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// empty partition
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ASSERT_EQUAL_QUIET(true, thrust::is_partitioned(v.begin(), v.begin(), ::cuda::std::identity{}));
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// one element true partition
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ASSERT_EQUAL_QUIET(true, thrust::is_partitioned(v.begin(), v.begin() + 1, ::cuda::std::identity{}));
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// just true partition
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ASSERT_EQUAL_QUIET(true, thrust::is_partitioned(v.begin(), v.begin() + 2, ::cuda::std::identity{}));
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// both true & false partitions
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ASSERT_EQUAL_QUIET(true, thrust::is_partitioned(v.begin(), v.end(), ::cuda::std::identity{}));
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// one element false partition
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ASSERT_EQUAL_QUIET(true, thrust::is_partitioned(v.begin() + 3, v.end(), ::cuda::std::identity{}));
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v = {1, 0, 1, 1};
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// not partitioned
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ASSERT_EQUAL_QUIET(false, thrust::is_partitioned(v.begin(), v.end(), ::cuda::std::identity{}));
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}
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DECLARE_VECTOR_UNITTEST(TestIsPartitionedSimple);
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template <class Vector>
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void TestIsPartitioned()
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{
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using T = typename Vector::value_type;
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const size_t n = (1 << 16) + 13;
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Vector v = unittest::random_integers<T>(n);
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v[0] = 1;
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v[1] = 0;
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ASSERT_EQUAL(false, thrust::is_partitioned(v.begin(), v.end(), is_even<T>()));
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thrust::partition(v.begin(), v.end(), is_even<T>());
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ASSERT_EQUAL(true, thrust::is_partitioned(v.begin(), v.end(), is_even<T>()));
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}
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DECLARE_INTEGRAL_VECTOR_UNITTEST(TestIsPartitioned);
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template <typename InputIterator, typename Predicate>
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bool is_partitioned(my_system& system, InputIterator /*first*/, InputIterator, Predicate)
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{
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system.validate_dispatch();
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return false;
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}
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void TestIsPartitionedDispatchExplicit()
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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::is_partitioned(sys, vec.begin(), vec.end(), 0);
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ASSERT_EQUAL(true, sys.is_valid());
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}
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DECLARE_UNITTEST(TestIsPartitionedDispatchExplicit);
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template <typename InputIterator, typename Predicate>
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bool is_partitioned(my_tag, InputIterator first, InputIterator, Predicate)
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{
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*first = 13;
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return false;
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}
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void TestIsPartitionedDispatchImplicit()
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{
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thrust::device_vector<int> vec(1);
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thrust::is_partitioned(thrust::retag<my_tag>(vec.begin()), thrust::retag<my_tag>(vec.end()), 0);
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ASSERT_EQUAL(13, vec.front());
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}
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DECLARE_UNITTEST(TestIsPartitionedDispatchImplicit);
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