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
95 lines
2.4 KiB
Plaintext
95 lines
2.4 KiB
Plaintext
#include <thrust/functional.h>
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#include <thrust/iterator/discard_iterator.h>
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#include <thrust/iterator/retag.h>
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#include <thrust/tabulate.h>
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#include <unittest/unittest.h>
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template <typename ForwardIterator, typename UnaryOperation>
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void tabulate(my_system& system, ForwardIterator, ForwardIterator, UnaryOperation)
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{
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system.validate_dispatch();
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}
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void TestTabulateDispatchExplicit()
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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::tabulate(sys, vec.begin(), vec.end(), ::cuda::std::identity{});
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ASSERT_EQUAL(true, sys.is_valid());
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}
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DECLARE_UNITTEST(TestTabulateDispatchExplicit);
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template <typename ForwardIterator, typename UnaryOperation>
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void tabulate(my_tag, ForwardIterator first, ForwardIterator, UnaryOperation)
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{
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*first = 13;
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}
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void TestTabulateDispatchImplicit()
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{
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thrust::device_vector<int> vec(1);
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thrust::tabulate(thrust::retag<my_tag>(vec.begin()), thrust::retag<my_tag>(vec.end()), ::cuda::std::identity{});
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ASSERT_EQUAL(13, vec.front());
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}
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DECLARE_UNITTEST(TestTabulateDispatchImplicit);
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template <class Vector>
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void TestTabulateSimple()
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{
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using namespace thrust::placeholders;
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Vector v(5);
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thrust::tabulate(v.begin(), v.end(), ::cuda::std::identity{});
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Vector ref{0, 1, 2, 3, 4};
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ASSERT_EQUAL(v, ref);
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thrust::tabulate(v.begin(), v.end(), -_1);
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ref = {0, -1, -2, -3, -4};
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ASSERT_EQUAL(v, ref);
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thrust::tabulate(v.begin(), v.end(), _1 * _1 * _1);
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ref = {0, 1, 8, 27, 64};
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ASSERT_EQUAL(v, ref);
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}
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DECLARE_VECTOR_UNITTEST(TestTabulateSimple);
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template <typename T>
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void TestTabulate(size_t n)
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{
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using namespace thrust::placeholders;
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thrust::host_vector<T> h_data(n);
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thrust::device_vector<T> d_data(n);
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thrust::tabulate(h_data.begin(), h_data.end(), _1 * _1 + 13);
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thrust::tabulate(d_data.begin(), d_data.end(), _1 * _1 + 13);
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ASSERT_EQUAL(h_data, d_data);
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thrust::tabulate(h_data.begin(), h_data.end(), (_1 - 7) * _1);
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thrust::tabulate(d_data.begin(), d_data.end(), (_1 - 7) * _1);
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ASSERT_EQUAL(h_data, d_data);
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}
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DECLARE_VARIABLE_UNITTEST(TestTabulate);
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template <typename T>
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void TestTabulateToDiscardIterator(size_t n)
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{
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thrust::tabulate(thrust::discard_iterator<thrust::device_system_tag>(),
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thrust::discard_iterator<thrust::device_system_tag>(static_cast<std::ptrdiff_t>(n)),
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::cuda::std::identity{});
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// nothing to check -- just make sure it compiles
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}
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DECLARE_VARIABLE_UNITTEST(TestTabulateToDiscardIterator);
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