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
66 lines
1.8 KiB
Plaintext
66 lines
1.8 KiB
Plaintext
#include <thrust/execution_policy.h>
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#include <thrust/transform_reduce.h>
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#include <unittest/unittest.h>
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#ifdef THRUST_TEST_DEVICE_SIDE
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template <typename ExecutionPolicy, typename Iterator1, typename Function1, typename T, typename Function2, typename Iterator2>
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__global__ void transform_reduce_kernel(
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ExecutionPolicy exec, Iterator1 first, Iterator1 last, Function1 f1, T init, Function2 f2, Iterator2 result)
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{
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*result = thrust::transform_reduce(exec, first, last, f1, init, f2);
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}
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template <typename ExecutionPolicy>
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void TestTransformReduceDevice(ExecutionPolicy exec)
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{
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using Vector = thrust::device_vector<int>;
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using T = typename Vector::value_type;
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Vector data{1, -2, 3};
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T init = 10;
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thrust::device_vector<T> result(1);
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transform_reduce_kernel<<<1, 1>>>(
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exec, data.begin(), data.end(), ::cuda::std::negate<T>(), init, ::cuda::std::plus<T>(), result.begin());
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cudaError_t const err = cudaDeviceSynchronize();
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ASSERT_EQUAL(cudaSuccess, err);
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ASSERT_EQUAL(8, (T) result[0]);
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}
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void TestTransformReduceDeviceSeq()
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{
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TestTransformReduceDevice(thrust::seq);
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}
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DECLARE_UNITTEST(TestTransformReduceDeviceSeq);
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void TestTransformReduceDeviceDevice()
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{
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TestTransformReduceDevice(thrust::device);
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}
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DECLARE_UNITTEST(TestTransformReduceDeviceDevice);
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#endif
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void TestTransformReduceCudaStreams()
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{
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using Vector = thrust::device_vector<int>;
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using T = Vector::value_type;
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Vector data{1, -2, 3};
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T init = 10;
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cudaStream_t s;
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cudaStreamCreate(&s);
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T result = thrust::transform_reduce(
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thrust::cuda::par.on(s), data.begin(), data.end(), ::cuda::std::negate<T>(), init, ::cuda::std::plus<T>());
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cudaStreamSynchronize(s);
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ASSERT_EQUAL(8, result);
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cudaStreamDestroy(s);
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}
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DECLARE_UNITTEST(TestTransformReduceCudaStreams);
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