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
58 lines
3.3 KiB
Plaintext
58 lines
3.3 KiB
Plaintext
#include <thrust/detail/allocator/allocator_system.h>
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#include <thrust/functional.h>
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#include <thrust/transform.h>
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#include <unittest/unittest.h>
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static const size_t num_samples = 10000;
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template <typename Vector, typename U>
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struct rebind_vector;
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template <typename T, typename U, typename Allocator>
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struct rebind_vector<thrust::host_vector<T, Allocator>, U>
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{
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using alloc_traits = typename cuda::std::allocator_traits<Allocator>;
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using new_alloc = typename alloc_traits::template rebind_alloc<U>;
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using type = thrust::host_vector<U, new_alloc>;
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};
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template <typename T, typename U, typename Allocator>
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struct rebind_vector<thrust::device_vector<T, Allocator>, U>
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{
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using type = thrust::device_vector<U, typename Allocator::template rebind<U>::other>;
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};
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template <typename T, typename U, typename Allocator>
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struct rebind_vector<thrust::universal_vector<T, Allocator>, U>
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{
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using type = thrust::universal_vector<U, typename Allocator::template rebind<U>::other>;
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};
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#define BINARY_FUNCTIONAL_PLACEHOLDERS_TEST(name, reference_operator, functor) \
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template <typename Vector> \
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void TestFunctionalPlaceholdersBinary##name() \
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{ \
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using T = typename Vector::value_type; \
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using bool_vector = typename rebind_vector<Vector, bool>::type; \
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Vector lhs = unittest::random_samples<T>(num_samples); \
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Vector rhs = unittest::random_samples<T>(num_samples); \
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\
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bool_vector reference(lhs.size()); \
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thrust::transform(lhs.begin(), lhs.end(), rhs.begin(), reference.begin(), functor<T>()); \
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\
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using namespace thrust::placeholders; \
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bool_vector result(lhs.size()); \
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thrust::transform(lhs.begin(), lhs.end(), rhs.begin(), result.begin(), _1 reference_operator _2); \
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\
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ASSERT_EQUAL(reference, result); \
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} \
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DECLARE_VECTOR_UNITTEST(TestFunctionalPlaceholdersBinary##name);
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BINARY_FUNCTIONAL_PLACEHOLDERS_TEST(EqualTo, ==, ::cuda::std::equal_to);
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BINARY_FUNCTIONAL_PLACEHOLDERS_TEST(NotEqualTo, !=, ::cuda::std::not_equal_to);
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BINARY_FUNCTIONAL_PLACEHOLDERS_TEST(Greater, >, ::cuda::std::greater);
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BINARY_FUNCTIONAL_PLACEHOLDERS_TEST(Less, <, ::cuda::std::less);
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BINARY_FUNCTIONAL_PLACEHOLDERS_TEST(GreaterEqual, >=, ::cuda::std::greater_equal);
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BINARY_FUNCTIONAL_PLACEHOLDERS_TEST(LessEqual, <=, ::cuda::std::less_equal);
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