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
7 lines
157 B
Plaintext
7 lines
157 B
Plaintext
CHECK: Before A->B Copy
|
|
CHECK-NEXT: A: 0 1 2 3 4
|
|
CHECK-NEXT: B: 0 0 0 0 0
|
|
CHECK-NEXT: After A->B Copy
|
|
CHECK-NEXT: A: 0 1 2 3 4
|
|
CHECK-NEXT: B: 0 1 2 3 4
|