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
60 lines
2.1 KiB
Plaintext
60 lines
2.1 KiB
Plaintext
//===----------------------------------------------------------------------===//
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//
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// Part of CUDASTF in CUDA C++ Core Libraries,
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// under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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// SPDX-FileCopyrightText: Copyright (c) 2022-2024 NVIDIA CORPORATION & AFFILIATES.
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//
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//===----------------------------------------------------------------------===//
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#include <cuda/experimental/__stf/stream/stream_ctx.cuh>
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#include <iostream>
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using namespace cuda::experimental::stf;
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int main()
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{
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stream_ctx ctx;
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// Contiguous 1D
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double* X = new double[1024];
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auto handle_X = ctx.logical_data(make_slice(X, 1024));
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// Contiguous 2D
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double* X2 = new double[1024 * 1024];
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auto handle_X2 = ctx.logical_data(make_slice(X2, std::tuple{1024, 1024}, 1024));
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// Contiguous 3D
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double* X4 = new double[128 * 128 * 128];
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auto handle_X4 = ctx.logical_data(make_slice(X4, std::tuple{128, 128, 128}, 128, 128 * 128));
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// Discontiguous 2D
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double* X3 = new double[128 * 8];
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auto handle_X3 = ctx.logical_data(make_slice(X3, std::tuple{64, 8}, 128));
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// Discontiguous 3D
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double* X5 = new double[32 * 4 * 4];
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auto handle_X5 = ctx.logical_data(make_slice(X5, std::tuple{16, 4, 4}, 32, 32 * 4));
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double* X6 = new double[32 * 4 * 4];
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auto handle_X6 = ctx.logical_data(make_slice(X6, std::tuple{32, 2, 4}, 32, 32 * 4));
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double* X7 = new double[128 * 128 * 128];
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cuda_safe_call(cudaHostRegister(X7, 128 * 128 * 128, cudaHostRegisterPortable));
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auto handle_X7 = ctx.logical_data(make_slice(X7, std::tuple{128, 128, 128}, 128, 128 * 128));
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// Detect that this was already pinned
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double* X9 = new double[1024];
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cuda_safe_call(cudaHostRegister(X9, 1024, cudaHostRegisterPortable));
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auto handle_X9 = ctx.logical_data(make_slice(X9, 1024));
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// Detect that this was already pinned
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double* X8 = new double[4 * 4 * 4];
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cuda_safe_call(cudaHostRegister(X8, 4 * 4 * 4, cudaHostRegisterPortable));
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auto handle_X8 = ctx.logical_data(make_slice(X8, std::tuple{1, 4, 4}, 4, 4 * 4));
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ctx.finalize();
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}
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