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
70 lines
1.9 KiB
Plaintext
70 lines
1.9 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.
|
|
//
|
|
//===----------------------------------------------------------------------===//
|
|
|
|
/**
|
|
* @file
|
|
*
|
|
* @brief Experiment with local context nesting
|
|
*
|
|
*/
|
|
|
|
#include <cuda/experimental/stf.cuh>
|
|
|
|
using namespace cuda::experimental::stf;
|
|
|
|
int main()
|
|
{
|
|
stackable_ctx ctx;
|
|
|
|
int array[1024];
|
|
for (size_t i = 0; i < 1024; i++)
|
|
{
|
|
array[i] = 1 + i * i;
|
|
}
|
|
|
|
auto lA = ctx.logical_data(array).set_symbol("A");
|
|
|
|
// repeat : {tmp = a; tmp*=2; a+=tmp}
|
|
for (size_t iter = 0; iter < 10; iter++)
|
|
{
|
|
stackable_ctx::graph_scope_guard graph{ctx}; // RAII: automatic push/pop (lock_guard style)
|
|
|
|
auto tmp = ctx.logical_data(lA.shape()).set_symbol("tmp");
|
|
|
|
ctx.parallel_for(tmp.shape(), tmp.write(), lA.read())->*[] __device__(size_t i, auto tmp, auto a) {
|
|
tmp(i) = a(i);
|
|
};
|
|
|
|
ctx.parallel_for(tmp.shape(), tmp.rw())->*[] __device__(size_t i, auto tmp) {
|
|
tmp(i) *= 2;
|
|
};
|
|
|
|
ctx.parallel_for(lA.shape(), tmp.read(), lA.rw())->*[] __device__(size_t i, auto tmp, auto a) {
|
|
a(i) += tmp(i);
|
|
};
|
|
|
|
// ctx.pop() is called automatically when 'graph' goes out of scope
|
|
}
|
|
|
|
ctx.finalize();
|
|
|
|
// Verify the array has been updated correctly by the write-back mechanism
|
|
// Each iteration transforms each element: a_new = a_old + 2 * a_old = 3 * a_old
|
|
// Starting from array[i] = 1 + i*i, after 10 iterations:
|
|
// array[i] = 3^10 * (1 + i*i)
|
|
constexpr int pow3_10 = 59049; // 3^10
|
|
|
|
for (size_t i = 0; i < 1024; i++)
|
|
{
|
|
int expected = pow3_10 * (1 + static_cast<int>(i * i));
|
|
EXPECT(array[i] == expected);
|
|
}
|
|
}
|