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
12 lines
272 B
Plaintext
12 lines
272 B
Plaintext
#include <cub/cub.cuh>
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void a()
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{
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printf("a() called\n");
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cub::DoubleBuffer<unsigned int> d_keys;
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cub::DoubleBuffer<cub::NullType> d_values;
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size_t temp_storage_bytes = 0;
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cub::DeviceRadixSort::SortPairs(nullptr, temp_storage_bytes, d_keys, d_values, 1024);
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}
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