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
16 lines
533 B
Plaintext
16 lines
533 B
Plaintext
// SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
|
|
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
|
|
|
|
// Tuning parameters found for signed integer types apply equally for unsigned integer types
|
|
|
|
#include <nvbench_helper.cuh>
|
|
|
|
// %RANGE% TUNE_ITEMS ipt 7:24:1
|
|
// %RANGE% TUNE_THREADS tpb 128:1024:32
|
|
// %RANGE% TUNE_TRANSPOSE trp 0:1:1
|
|
// %RANGE% TUNE_LOAD ld 0:1:1
|
|
// %RANGE% TUNE_MAX_SEGMENTS_PER_BLOCK spb 1:512:511
|
|
|
|
using op_t = ::cuda::std::plus<>;
|
|
#include "base.cuh"
|