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
23 lines
432 B
Plaintext
23 lines
432 B
Plaintext
#include <thrust/execution_policy.h>
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#include <thrust/system/cuda/detail/util.h>
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#include <thread>
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#include <unittest/unittest.h>
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void verify_stream()
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{
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auto exec = thrust::device;
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auto stream = thrust::cuda_cub::stream(exec);
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ASSERT_EQUAL(stream, cudaStreamPerThread);
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}
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void TestPerThreadDefaultStream()
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{
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verify_stream();
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std::thread t(verify_stream);
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t.join();
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}
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DECLARE_UNITTEST(TestPerThreadDefaultStream);
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