dedf08166a
Added 863 files from NVIDIA/cccl sparse checkout: - c2h/ (27 files): Catch2 test helpers — generators, validators, runner - nvbench_helper/ (10 files): Benchmark harness utilities - cmake/ (29 files): CMake presets and build helpers - cudax/ (794 files): Experimental CUDA extensions - AGENTS.md: NVIDIA's official AI agent instructions for CCCL - CMakePresets.json: Standardized build configurations - cccl-version.json: Version tracking Also added CCCL_ASSET_MAP.md mapping all 4295 CCCL files to competition value and PRD items. cccl_upstream now covers 100% of competition-critical assets: - 27 tuning headers (SM80/90/100 benchmark data) - 32 dispatch headers (algorithm implementations) - 60 Thrust examples (correctness verification) - 217 CUB Catch2 tests (regression matrix) - 153 CUB benchmarks (parameter space search) - 18 CUB examples (API verification) - 27 test helpers + benchmark harness - 794 cudax experimental extensions
75 lines
1.8 KiB
Plaintext
75 lines
1.8 KiB
Plaintext
//===----------------------------------------------------------------------===//
|
|
//
|
|
// 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.
|
|
//
|
|
//===----------------------------------------------------------------------===//
|
|
|
|
#include <cuda/experimental/__stf/graph/graph_ctx.cuh>
|
|
|
|
#include <iostream>
|
|
|
|
#if !_CCCL_COMPILER(MSVC)
|
|
using namespace cuda::experimental::stf;
|
|
|
|
__global__ void kernel()
|
|
{
|
|
// No-op
|
|
}
|
|
#endif // !_CCCL_COMPILER(MSVC)
|
|
|
|
int main([[maybe_unused]] int argc, [[maybe_unused]] char** argv)
|
|
{
|
|
// TODO fix setenv
|
|
#if !_CCCL_COMPILER(MSVC)
|
|
int nblocks = 4;
|
|
size_t block_size = 1024 * 1024;
|
|
|
|
if (argc > 1)
|
|
{
|
|
nblocks = atoi(argv[1]);
|
|
}
|
|
|
|
if (argc > 2)
|
|
{
|
|
block_size = atoi(argv[2]);
|
|
}
|
|
|
|
// At most 1 buffer is allocated at the same time
|
|
setenv("MAX_ALLOC_CNT", "1", 0);
|
|
|
|
graph_ctx ctx;
|
|
|
|
::std::vector<logical_data<slice<char>>> handles(nblocks);
|
|
|
|
char* h_buffer = new char[nblocks * block_size];
|
|
|
|
for (int i = 0; i < nblocks; i++)
|
|
{
|
|
handles[i] = ctx.logical_data(make_slice(&h_buffer[i * block_size], block_size));
|
|
handles[i].set_symbol("D_" + std::to_string(i));
|
|
}
|
|
|
|
// We only 2 buffers, we are forced to reuse the buffer from D0 for D2
|
|
for (int i = 0; i < 3; i++)
|
|
{
|
|
ctx.task(handles[i % nblocks].rw())->*[&](cudaStream_t s, auto /*unused*/) {
|
|
kernel<<<1, 1, 0, s>>>();
|
|
};
|
|
}
|
|
|
|
ctx.submit();
|
|
|
|
if (argc > 3)
|
|
{
|
|
std::cout << "Generating DOT output in " << argv[3] << '\n';
|
|
ctx.print_to_dot(argv[1]);
|
|
}
|
|
|
|
ctx.finalize();
|
|
#endif // !_CCCL_COMPILER(MSVC)
|
|
}
|