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
374 B
Plaintext
11 lines
374 B
Plaintext
CHECK: ******Summary Statistics Example*****
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CHECK-NEXT: The data: 4 7 13 16
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CHECK-NEXT: Count : 4
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CHECK-NEXT: Minimum : 4
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CHECK-NEXT: Maximum : 16
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CHECK-NEXT: Mean : 10
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CHECK-NEXT: Variance : 30
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CHECK-NEXT: Standard Deviation : 4.74342
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CHECK-NEXT: Skewness : 0
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CHECK-NEXT: Kurtosis : 1.36
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