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
76 lines
2.1 KiB
C++
76 lines
2.1 KiB
C++
#include <thrust/device_ptr.h>
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#include <thrust/reduce.h>
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#include <thrust/scan.h>
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#include <thrust/sort.h>
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#include <thrust/system_error.h>
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#include <thrust/transform.h>
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#include <unittest/unittest.h>
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void TestNvccIndependenceTransform()
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{
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using T = int;
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const int n = 10;
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thrust::host_vector<T> h_input = unittest::random_integers<T>(n);
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thrust::device_vector<T> d_input = h_input;
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thrust::host_vector<T> h_output(n);
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thrust::device_vector<T> d_output(n);
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thrust::transform(h_input.begin(), h_input.end(), h_output.begin(), ::cuda::std::negate<T>());
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thrust::transform(d_input.begin(), d_input.end(), d_output.begin(), ::cuda::std::negate<T>());
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ASSERT_EQUAL(h_output, d_output);
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}
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DECLARE_UNITTEST(TestNvccIndependenceTransform);
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void TestNvccIndependenceReduce()
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{
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using T = int;
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const int n = 10;
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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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T init = 13;
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T h_result = thrust::reduce(h_data.begin(), h_data.end(), init);
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T d_result = thrust::reduce(d_data.begin(), d_data.end(), init);
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ASSERT_ALMOST_EQUAL(h_result, d_result);
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}
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DECLARE_UNITTEST(TestNvccIndependenceReduce);
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void TestNvccIndependenceExclusiveScan()
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{
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using T = int;
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const int n = 10;
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thrust::host_vector<T> h_input = unittest::random_integers<T>(n);
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thrust::device_vector<T> d_input = h_input;
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thrust::host_vector<T> h_output(n);
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thrust::device_vector<T> d_output(n);
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thrust::inclusive_scan(h_input.begin(), h_input.end(), h_output.begin());
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thrust::inclusive_scan(d_input.begin(), d_input.end(), d_output.begin());
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ASSERT_EQUAL(d_output, h_output);
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}
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DECLARE_UNITTEST(TestNvccIndependenceExclusiveScan);
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void TestNvccIndependenceSort()
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{
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using T = int;
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const int n = 10;
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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_UNITTEST(TestNvccIndependenceSort);
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