[CCCL] 瘦身 + 补全: 移除 cudax/python/libcudacxx-tests 冗余文件, 新增 c2h 测试助手 + cmake 构建系统 + 8 个 CUDA thrust examples
变更摘要:
- 删除: cudax/ (783 files, 7.2M) — 实验性组件,竞赛不需要
- 删除: python/ (226 files, 2.0M) — Python 绑定,竞赛不需要
- 删除: libcudacxx/{test,benchmarks,codegen,cmake,share} (4432 files, 31M)
保留: libcudacxx/include/ (1463 headers, cuda::std 编译依赖)
- 新增: c2h/ (27 files) — CUB Catch2 测试辅助头文件,编译 243 个测试必需
- 新增: cmake/ (29 files) — CCCL 原生 CMake 构建系统
- 新增: thrust/examples/cuda/ (7 files) + cpp_integration/ (1 file)
async_reduce, custom_temporary_allocation, explicit_cuda_stream,
global_device_vector, range_view, unwrap_pointer, wrap_pointer, device
结果: cccl_upstream 从 74M→35M (瘦身 53%), 核心内容 100% 保留:
27/27 tuning headers, 78 benchmarks, 243 tests,
60 thrust examples, 18 CUB examples, 全部编译头文件
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@@ -1,67 +0,0 @@
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//===----------------------------------------------------------------------===//
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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/interfaces/slice_reduction_ops.cuh>
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#include <cuda/experimental/__stf/stream/stream_ctx.cuh>
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using namespace cuda::experimental::stf;
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using scalar_t = slice_stream_interface<int, 1>;
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template <typename T>
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__global__ void set_value(T* addr, T val)
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{
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*addr = val;
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}
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template <typename T>
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__global__ void check_value_and_reset(T* addr, T val, T reset_val)
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{
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assert(*addr == val);
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*addr = reset_val;
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}
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template <typename T>
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__global__ void add_val(T* inout_addr, T val)
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{
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*inout_addr += val;
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}
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int main()
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{
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stream_ctx ctx;
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const int N = 4;
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auto var_handle = ctx.logical_data(shape_of<slice<int>>(1));
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var_handle.set_symbol("var");
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auto redux_op = std::make_shared<slice_reduction_op_sum<int>>();
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const int niters = 4;
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for (int iter = 0; iter < niters; iter++)
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{
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// We add i (total = N(N-1)/2 + initial_value)
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for (int i = 0; i < N; i++)
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{
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ctx.task(var_handle.relaxed(redux_op))->*[=](cudaStream_t stream, auto d_var) {
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add_val<<<1, 1, 0, stream>>>(d_var.data_handle(), i);
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cuda_safe_call(cudaGetLastError());
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};
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}
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// Check that we have the expected value, and reset it so that we can perform another reduction
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ctx.task(var_handle.rw())->*[=](cudaStream_t stream, auto d_var) {
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int expected = (N * (N - 1)) / 2;
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check_value_and_reset<<<1, 1, 0, stream>>>(d_var.data_handle(), expected, 0);
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};
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}
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ctx.finalize();
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}
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