Files
project_6/cccl_upstream/cudax/test/stf/stress/many_read.cu
muh-bot dedf08166a [CCCL] Add missing CCCL components: c2h, nvbench_helper, cmake, cudax, AGENTS.md
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
2026-08-06 02:14:18 +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.
//
//===----------------------------------------------------------------------===//
#include <cuda/experimental/stf.cuh>
#include <chrono>
using namespace std::chrono;
using namespace cuda::experimental::stf;
/* wall-clock time */
double gettime()
{
auto now = system_clock::now().time_since_epoch();
return duration_cast<duration<double>>(now).count();
}
int main(int argc, char** argv)
{
stream_ctx ctx;
const size_t N = 16;
double X[N], Y[N];
for (size_t i = 0; i < N; i++)
{
X[i] = 1.0;
Y[i] = 2.0;
}
auto lX = ctx.logical_data(X);
auto lY = ctx.logical_data(Y);
size_t nloops = 10;
size_t inner_nloops = 1000;
if (argc > 1)
{
nloops = atol(argv[1]);
}
if (argc > 2)
{
inner_nloops = atol(argv[2]);
}
for (size_t j = 0; j < nloops; j++)
{
std::chrono::steady_clock::time_point start, stop;
start = std::chrono::steady_clock::now();
for (size_t i = 0; i < inner_nloops; i++)
{
ctx.task(lX.read(), lY.rw())->*[](cudaStream_t, auto, auto) {};
}
stop = std::chrono::steady_clock::now();
std::chrono::duration<double> duration = stop - start;
fprintf(stderr, "Elapsed: %.2lf us per task\n", duration.count() * 1000000.0 / (inner_nloops));
}
ctx.finalize();
}