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
125 lines
3.1 KiB
Plaintext
125 lines
3.1 KiB
Plaintext
#include <thrust/execution_policy.h>
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#include <thrust/reduce.h>
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#include <cuda/iterator>
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#include <unittest/unittest.h>
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template <typename ExecutionPolicy, typename InputIter, typename OutputIter, typename T>
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__global__ void reduce_into_kernel(ExecutionPolicy exec, InputIter first, InputIter last, OutputIter result, T init)
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{
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thrust::reduce_into(exec, first, last, result, init);
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}
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#ifdef THRUST_TEST_DEVICE_SIDE
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template <typename T, typename ExecutionPolicy>
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void TestReduceIntoDevice(ExecutionPolicy exec, 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::host_vector<T> h_result(1);
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thrust::device_vector<T> d_result(1);
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T init = 13;
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thrust::reduce_into(h_data.begin(), h_data.end(), h_result.begin(), init);
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reduce_into_kernel<<<1, 1>>>(exec, d_data.begin(), d_data.end(), d_result.begin(), init);
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cudaError_t const err = cudaDeviceSynchronize();
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ASSERT_EQUAL(cudaSuccess, err);
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ASSERT_EQUAL(h_result, d_result);
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}
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template <typename T>
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struct TestReduceIntoDeviceSeq
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{
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void operator()(const size_t n)
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{
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TestReduceIntoDevice<T>(thrust::seq, n);
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}
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};
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VariableUnitTest<TestReduceIntoDeviceSeq, IntegralTypes> TestReduceIntoDeviceSeqInstance;
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template <typename T>
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struct TestReduceIntoDeviceDevice
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{
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void operator()(const size_t n)
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{
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TestReduceIntoDevice<T>(thrust::device, n);
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}
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};
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VariableUnitTest<TestReduceIntoDeviceDevice, IntegralTypes> TestReduceIntoDeviceDeviceInstance;
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template <typename T>
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struct TestReduceIntoDeviceNoSync
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{
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void operator()(const size_t n)
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{
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TestReduceIntoDevice<T>(thrust::cuda::par_nosync, n);
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}
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};
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VariableUnitTest<TestReduceIntoDeviceNoSync, IntegralTypes> TestReduceIntoDeviceNoSyncInstance;
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#endif
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template <typename ExecutionPolicy>
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void TestReduceIntoCudaStreams(ExecutionPolicy policy)
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{
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using Vector = thrust::device_vector<int>;
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Vector v = {1, -2, 3};
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Vector o(1);
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cudaStream_t s;
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cudaStreamCreate(&s);
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auto streampolicy = policy.on(s);
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// no initializer
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thrust::reduce_into(streampolicy, v.begin(), v.end(), o.begin());
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cudaStreamSynchronize(s);
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ASSERT_EQUAL(o[0], 2);
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// with initializer
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thrust::reduce_into(streampolicy, v.begin(), v.end(), o.begin(), 10);
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cudaStreamSynchronize(s);
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ASSERT_EQUAL(o[0], 12);
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cudaStreamDestroy(s);
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}
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void TestReduceIntoCudaStreamsSync()
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{
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TestReduceIntoCudaStreams(thrust::cuda::par);
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}
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DECLARE_UNITTEST(TestReduceIntoCudaStreamsSync);
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void TestReduceIntoCudaStreamsNoSync()
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{
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TestReduceIntoCudaStreams(thrust::cuda::par_nosync);
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}
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DECLARE_UNITTEST(TestReduceIntoCudaStreamsNoSync);
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#if defined(THRUST_RDC_ENABLED)
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void TestReduceIntoLargeInput()
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{
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using T = unsigned long long;
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using OffsetT = std::size_t;
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const OffsetT num_items = 1ull << 32;
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cuda::constant_iterator<T> d_data(T{1});
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thrust::device_vector<T> d_result(1);
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reduce_into_kernel<<<1, 1>>>(thrust::device, d_data, d_data + num_items, d_result.begin(), T{});
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cudaError_t const err = cudaDeviceSynchronize();
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ASSERT_EQUAL(cudaSuccess, err);
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ASSERT_EQUAL(num_items, d_result[0]);
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}
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DECLARE_UNITTEST(TestReduceIntoLargeInput);
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#endif
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