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
9 lines
346 B
Plaintext
9 lines
346 B
Plaintext
CHECK: Set A [ 0 2 4 5 6 8 9 ]
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CHECK-NEXT: Set B [ 0 1 2 3 5 7 8 ]
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CHECK-NEXT: Merge(A,B) [ 0 0 1 2 2 3 4 5 5 6 7 8 8 9 ]
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CHECK-NEXT: Union(A,B) [ 0 1 2 3 4 5 6 7 8 9 ]
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CHECK-NEXT: Intersection(A,B) [ 0 2 5 8 ]
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CHECK-NEXT: Difference(A,B) [ 4 6 9 ]
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CHECK-NEXT: SymmetricDifference(A,B) [ 1 3 4 6 7 9 ]
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CHECK-NEXT: SetIntersectionSize(A,B) 4
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