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
17 lines
932 B
Plaintext
17 lines
932 B
Plaintext
CHECK: Inclusive Segmented Scan w/ Key Sequence
|
|
CHECK-NEXT: keys : 0 0 0 1 1 2 2 2 2 3 4 4 5 5 5
|
|
CHECK-NEXT: input values : 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
|
|
CHECK-NEXT: output values : 2 4 6 2 4 2 4 6 8 2 2 4 2 4 6
|
|
CHECK: Inclusive Segmented Scan w/ Head Flag Sequence
|
|
CHECK-NEXT: head flags : 1 0 0 1 0 1 0 0 0 1 1 0 1 0 0
|
|
CHECK-NEXT: input values : 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
|
|
CHECK-NEXT: output values : 2 4 6 2 4 2 4 6 8 2 2 4 2 4 6
|
|
CHECK: Exclusive Segmented Scan w/ Key Sequence
|
|
CHECK-NEXT: keys : 0 0 0 1 1 2 2 2 2 3 4 4 5 5 5
|
|
CHECK-NEXT: input values : 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
|
|
CHECK-NEXT: output values : 0 2 4 0 2 0 2 4 6 0 0 2 0 2 4
|
|
CHECK: Exclusive Segmented Scan w/ Head Flag Sequence
|
|
CHECK-NEXT: head flags : 1 0 0 1 0 1 0 0 0 1 1 0 1 0 0
|
|
CHECK-NEXT: input values : 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
|
|
CHECK-NEXT: output values : 0 2 4 0 2 0 2 4 6 0 0 2 0 2 4
|