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
17 lines
377 B
Plaintext
17 lines
377 B
Plaintext
#include <cuda/std/memory>
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#include <cuda_runtime_api.h>
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#include <unittest/unittest.h>
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template <typename T>
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void TestCudaMallocResultAligned(const std::size_t n)
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{
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T* ptr = nullptr;
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cudaMalloc(&ptr, n * sizeof(T));
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cudaFree(ptr);
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ASSERT_EQUAL(true, ::cuda::std::is_sufficiently_aligned<alignof(T)>(ptr));
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}
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DECLARE_VARIABLE_UNITTEST(TestCudaMallocResultAligned);
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