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
11 lines
231 B
Plaintext
11 lines
231 B
Plaintext
// %PARAM% TEST_ERR err 0:1
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int main()
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{
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#if TEST_ERR == 0
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static_assert(false, "fail one"); // expected-error-0 {{"fail one"}}
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#elif TEST_ERR == 1
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static_assert(false, "fail two"); // expected-error-1 {{"fail two"}}
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#endif
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}
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