project_6/cccl_upstream/cudax/cmake/stf_header_unittest.in.cu

// This file is autogenerated by configuring stf_header_unittest.in.cu.

// clang-format off
#define UNITTESTED_FILE "@source@"

#include <cuda/experimental/__stf/utility/unittest.cuh>

#include <@source@>
//clang-format on
[INFRA] Import NVIDIA/CCCL upstream as optimization reference library 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 2026-07-30 09:35:51 +00:00			`// This file is autogenerated by configuring stf_header_unittest.in.cu.`

			`// clang-format off`
			`#define UNITTESTED_FILE "@source@"`

			`#include <cuda/experimental/__stf/utility/unittest.cuh>`

			`#include <@source@>`
			`//clang-format on`