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project_6/cccl_upstream/cudax/test/stf/dot/sections.cu
EngineX CI 56fd68e7dd [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

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//===----------------------------------------------------------------------===//
//
// Part of CUDASTF in CUDA C++ Core Libraries,
// under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
// SPDX-FileCopyrightText: Copyright (c) 2022-2024 NVIDIA CORPORATION & AFFILIATES.
//
//===----------------------------------------------------------------------===//
/**
* @file
* @brief This test makes sure we can generate a dot file with sections
*/
#include <cuda/experimental/stf.cuh>
using namespace cuda::experimental::stf;
int main()
{
// TODO (miscco): Make it work for windows
#if !_CCCL_COMPILER(MSVC)
// Generate a random filename
int r = rand();
char filename[64];
snprintf(filename, 64, "output_%d.dot", r);
// fprintf(stderr, "filename %s\n", filename);
setenv("CUDASTF_DOT_FILE", filename, 1);
context ctx;
auto lA = ctx.logical_data(shape_of<slice<char>>(64));
auto lB = ctx.logical_data(shape_of<slice<char>>(64));
auto lC = ctx.logical_data(shape_of<slice<char>>(64));
ctx.task(lA.write()).set_symbol("initA")->*[](cudaStream_t, auto) {};
ctx.task(lB.write()).set_symbol("initB")->*[](cudaStream_t, auto) {};
ctx.task(lC.write()).set_symbol("initC")->*[](cudaStream_t, auto) {};
for (size_t j = 0; j < 3; j++)
{
ctx.task(lA.rw()).set_symbol("f1")->*[](cudaStream_t, auto) {};
auto guard = ctx.dot_section("sec_loop " + ::std::to_string(j));
for (size_t i = 0; i < 2; i++)
{
auto guard_inner = ctx.dot_section("sec_inner_loop " + ::std::to_string(i));
ctx.task(lA.read(), lB.rw()).set_symbol("f2")->*[](cudaStream_t, auto, auto) {};
ctx.task(lA.read(), lC.rw()).set_symbol("f2")->*[](cudaStream_t, auto, auto) {};
ctx.task(lB.read(), lC.read(), lA.rw()).set_symbol("f3")->*[](cudaStream_t, auto, auto, auto) {};
}
}
ctx.finalize();
// Call this explicitly for the purpose of the test
reserved::dot::instance().finish();
// Make sure the file exists, and erase it
// fprintf(stderr, "ERASE. ...\n");
EXPECT(access(filename, F_OK) != -1);
EXPECT(unlink(filename) == 0);
#endif // !_CCCL_COMPILER(MSVC)
}