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
18 lines
406 B
Plaintext
18 lines
406 B
Plaintext
#include <thrust/copy.h>
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#include <thrust/device_vector.h>
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#include <thrust/sort.h>
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#include "device.h"
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void sort_on_device(thrust::host_vector<int>& h_vec)
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{
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// transfer data to the device
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thrust::device_vector<int> d_vec = h_vec;
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// sort data on the device
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thrust::sort(d_vec.begin(), d_vec.end());
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// transfer data back to host
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thrust::copy(d_vec.begin(), d_vec.end(), h_vec.begin());
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}
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