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
15 lines
463 B
YAML
15 lines
463 B
YAML
---
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InheritParentConfig: true
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CheckOptions:
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- key: modernize-loop-convert.MaxCopySize
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value: '16'
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- key: modernize-loop-convert.MinConfidence
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value: reasonable
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- key: modernize-pass-by-value.IncludeStyle
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value: llvm
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- key: modernize-replace-auto-ptr.IncludeStyle
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value: llvm
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- key: modernize-use-nullptr.NullMacros
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value: 'NULL'
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...
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