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[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

Browse Source 
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
This commit is contained in:
muh-bot
2026-08-03 12:39:26 +00:00
parent a2a5dd8f00
commit 24ef6a91b5
5439 changed files with 0 additions and 719516 deletions
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441
cccl_upstream/cudax/test/fill_bytes/fill_bytes_mdspan.cu
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@@ -1,441 +0,0 @@
//===----------------------------------------------------------------------===//
//
// Part of CUDA Experimental 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) 2026 NVIDIA CORPORATION & AFFILIATES.
//
//===----------------------------------------------------------------------===//
#include <thrust/device_vector.h>
#include <thrust/host_vector.h>
#include <cuda/mdspan>
#include <cuda/std/array>
#include <cuda/std/cstddef>
#include <cuda/std/cstdint>
#include <cuda/std/span>
#include <cuda/stream>
#include <cuda/experimental/fill_bytes.cuh>
#include <cstring>
#include <stdexcept>
#include "testing.cuh"
static const cuda::stream stream{cuda::device_ref{0}};
using host_vector_bytes_t = thrust::host_vector<cuda::std::byte>;
using span_bytes_t = cuda::std::span<const cuda::std::byte>;
template <typename Value>
void fill_expected_bytes(host_vector_bytes_t& expected, size_t byte_offset, size_t num_bytes, const Value& value)
{
cuda::std::byte pattern[sizeof(Value)];
std::memcpy(pattern, &value, sizeof(Value));
for (size_t i = 0; i < num_bytes; ++i)
{
expected[byte_offset + i] = pattern[i % sizeof(Value)];
}
}
// create a host vector of bytes with a repeated pattern
template <typename Value>
host_vector_bytes_t repeated_bytes_vector(size_t num_bytes, const Value& value)
{
host_vector_bytes_t expected(num_bytes);
fill_expected_bytes(expected, 0, num_bytes, value);
return expected;
}
template <typename Tp>
span_bytes_t to_byte_span(const thrust::host_vector<Tp>& data)
{
return cuda::std::as_bytes(cuda::std::span<const Tp>{data.data(), data.size()});
}
// create a copy of the input as a host vector of bytes
template <typename Tp>
host_vector_bytes_t to_byte_vector(const thrust::host_vector<Tp>& data)
{
auto data_bytes = to_byte_span(data);
host_vector_bytes_t bytes(data_bytes.size());
for (size_t i = 0; i < data_bytes.size(); ++i)
{
bytes[i] = data_bytes[i];
}
return bytes;
}
bool equal_bytes(span_bytes_t lhs, span_bytes_t rhs)
{
if (lhs.size() != rhs.size())
{
return false;
}
for (size_t i = 0; i < lhs.size(); ++i)
{
if (lhs[i] != rhs[i])
{
return false;
}
}
return true;
}
template <typename Tp>
thrust::host_vector<Tp> make_host_data(size_t size, uint8_t byte)
{
thrust::host_vector<Tp> data(size);
::std::memset(data.data(), byte, data.size() * sizeof(Tp));
return data;
}
template <typename Tp, typename Value>
host_vector_bytes_t contiguous_fill_bytes(size_t num_elements, Value value)
{
return repeated_bytes_vector(num_elements * sizeof(Tp), value);
}
template <typename Tp, typename Value>
void fill_expected_element(host_vector_bytes_t& expected, size_t element_offset, Value value)
{
fill_expected_bytes(expected, element_offset * sizeof(Tp), sizeof(Tp), value);
}
// contiguous layout tests
template <typename _Layout = cuda::std::layout_right, typename Tp, typename Value, typename Index, size_t... Extents>
void test_impl(const thrust::host_vector<Tp>& input,
const host_vector_bytes_t& expected,
cuda::std::extents<Index, Extents...> extents,
Value value)
{
using extents_t = cuda::std::extents<Index, Extents...>;
using mapping_t = typename _Layout::template mapping<extents_t>;
thrust::device_vector<Tp> device_data(input.begin(), input.end());
cuda::device_mdspan<Tp, extents_t, _Layout> dst(thrust::raw_pointer_cast(device_data.data()), mapping_t(extents));
cuda::experimental::fill_bytes(dst, value, stream);
stream.sync();
const thrust::host_vector<Tp> actual(device_data);
REQUIRE(equal_bytes(to_byte_span(actual), to_byte_span(expected)));
}
// layout_stride tests
template <typename Tp, typename Value, typename Index, size_t... Extents>
void test_impl_stride(
const thrust::host_vector<Tp>& input,
const host_vector_bytes_t& expected,
const cuda::std::extents<Index, Extents...>& extents,
const cuda::std::array<Index, sizeof...(Extents)>& strides,
Value value,
size_t offset = 0)
{
using extents_t = cuda::std::extents<Index, Extents...>;
using mapping_t = cuda::std::layout_stride::mapping<extents_t>;
thrust::device_vector<Tp> device_data(input.begin(), input.end());
cuda::device_mdspan<Tp, extents_t, cuda::std::layout_stride> dst(
thrust::raw_pointer_cast(device_data.data()) + offset, mapping_t(extents, strides));
cuda::experimental::fill_bytes(dst, value, stream);
stream.sync();
const thrust::host_vector<Tp> actual(device_data);
REQUIRE(equal_bytes(to_byte_span(actual), to_byte_span(expected)));
}
// layout_stride_relaxed tests
template <typename Tp, typename Value, typename Index, size_t... Extents>
void test_impl_relaxed(
const thrust::host_vector<Tp>& input,
const host_vector_bytes_t& expected,
const cuda::std::extents<Index, Extents...>& extents,
const cuda::dstrides<Index, sizeof...(Extents)>& strides,
Index offset,
Value value)
{
using extents_t = cuda::std::extents<Index, Extents...>;
using mapping_t = cuda::layout_stride_relaxed::mapping<extents_t>;
thrust::device_vector<Tp> device_data(input.begin(), input.end());
cuda::device_mdspan<Tp, extents_t, cuda::layout_stride_relaxed> dst(
thrust::raw_pointer_cast(device_data.data()), mapping_t(extents, strides, offset));
cuda::experimental::fill_bytes(dst, value, stream);
stream.sync();
const thrust::host_vector<Tp> actual(device_data);
REQUIRE(equal_bytes(to_byte_span(actual), to_byte_span(expected)));
}
/***********************************************************************************************************************
* 1D Tests
**********************************************************************************************************************/
enum class pattern32 : uint32_t
{
value = 0xff00ff00u,
};
TEST_CASE("fill_bytes device mdspan accepts generic fill values", "[fill_bytes][device]")
{
constexpr int n = 16427;
using extents_t = cuda::std::extents<int, n>;
// int16_t
{
auto input = make_host_data<int16_t>(n, 0xCD);
constexpr int16_t value = -0x1234;
test_impl(input, contiguous_fill_bytes<int16_t>(n, value), extents_t{}, value);
}
// std::byte
{
auto input = make_host_data<uint8_t>(n, 0xCD);
constexpr auto value = cuda::std::byte{0xAB};
test_impl(input, contiguous_fill_bytes<uint8_t>(n, value), extents_t{}, value);
}
// int
{
auto input = make_host_data<int>(n, 0xCD);
constexpr auto value = pattern32::value;
test_impl(input, contiguous_fill_bytes<int>(n, value), extents_t{}, value);
}
// float
{
auto input = make_host_data<float>(n, 0xCD);
constexpr int value = 0xAB;
test_impl(input, contiguous_fill_bytes<float>(n, value), extents_t{}, value);
}
}
TEST_CASE("fill_bytes handles layout_stride_relaxed negative strides and offsets", "[fill_bytes][relaxed]")
{
constexpr int n = 8455;
using extents_t = cuda::std::extents<int, n>;
using mapping_t = cuda::layout_stride_relaxed::mapping<extents_t>;
// int8_t
{
auto input = make_host_data<uint8_t>(n, 0xCD);
const mapping_t mapping(extents_t{}, cuda::dstrides<int, 1>(-1), n - 1);
const uint8_t value = 0x5A;
test_impl_relaxed(input, contiguous_fill_bytes<uint8_t>(n, value), extents_t{}, mapping.strides(), n - 1, value);
}
// uint32_t pattern into int64_t elements
{
auto input = make_host_data<int64_t>(n, 0xCD);
const mapping_t mapping(extents_t{}, cuda::dstrides<int, 1>(-1), n - 1);
const uint32_t value = 0x12345678;
test_impl_relaxed(input, contiguous_fill_bytes<int64_t>(n, value), extents_t{}, mapping.strides(), n - 1, value);
}
}
/***********************************************************************************************************************
* 2D Tests
**********************************************************************************************************************/
TEST_CASE("fill_bytes handles layout_left device mdspan", "[fill_bytes][layout_left]")
{
constexpr int rows = 265;
constexpr int cols = 456;
using extents_t = cuda::std::extents<int, rows, cols>;
auto input = make_host_data<uint16_t>(rows * cols, 0xCD);
const uint16_t value = 0x1234;
test_impl<cuda::std::layout_left>(input, contiguous_fill_bytes<uint16_t>(rows * cols, value), extents_t{}, value);
}
TEST_CASE("fill_bytes handles singleton dimensions", "[fill_bytes][singleton]")
{
constexpr int rows = 2;
constexpr int cols = 4;
using extents_t = cuda::std::extents<int, rows, 1, cols>;
auto input = make_host_data<uint16_t>(rows * cols, 0xCD);
constexpr auto value = uint16_t{0x1234};
test_impl(input, contiguous_fill_bytes<uint16_t>(rows * cols, value), extents_t{}, value);
test_impl<cuda::std::layout_left>(input, contiguous_fill_bytes<uint16_t>(rows * cols, value), extents_t{}, value);
}
TEST_CASE("fill_bytes preserves padding bytes in strided row-major destination layouts", "[fill_bytes][stride]")
{
constexpr int rows = 367;
constexpr int cols = 456;
constexpr int ld = 657;
using extents_t = cuda::std::extents<int, rows, cols>;
using mapping_t = cuda::std::layout_stride::mapping<extents_t>;
cuda::std::array<int, 2> strides{ld, 1};
mapping_t mapping(extents_t{}, strides);
auto input = make_host_data<uint16_t>(mapping.required_span_size(), 0xCD);
uint16_t value = 0x1234;
auto expected = to_byte_vector(input);
for (int row = 0; row < rows; ++row)
{
for (int col = 0; col < cols; ++col)
{
fill_expected_element<uint16_t>(expected, row * ld + col, value);
}
}
test_impl_stride(input, expected, extents_t{}, strides, value);
}
TEST_CASE("fill_bytes preserves padding bytes in strided column-major destination layouts", "[fill_bytes][stride]")
{
constexpr int rows = 127;
constexpr int cols = 79;
constexpr int ld = 191;
using extents_t = cuda::std::extents<int, rows, cols>;
using mapping_t = cuda::std::layout_stride::mapping<extents_t>;
cuda::std::array<int, 2> strides{1, ld};
mapping_t mapping(extents_t{}, strides);
auto input = make_host_data<uint16_t>(mapping.required_span_size(), 0xCD);
uint16_t value = 0x1234;
auto expected = to_byte_vector(input);
for (int row = 0; row < rows; ++row)
{
for (int col = 0; col < cols; ++col)
{
fill_expected_element<uint16_t>(expected, row + col * ld, value);
}
}
test_impl_stride(input, expected, extents_t{}, strides, value);
}
/***********************************************************************************************************************
* 3D Tests
**********************************************************************************************************************/
TEST_CASE("fill_bytes handles 3D mdspans", "[fill_bytes][3d]")
{
constexpr int dim0 = 2;
constexpr int dim1 = 3;
constexpr int dim2 = 4;
constexpr int total = dim0 * dim1 * dim2;
using extents_t = cuda::std::extents<int, dim0, dim1, dim2>;
auto input = make_host_data<uint32_t>(total, 0xCD);
constexpr auto value = pattern32::value;
test_impl(input, contiguous_fill_bytes<uint32_t>(total, value), extents_t{}, value);
test_impl<cuda::std::layout_left>(input, contiguous_fill_bytes<uint32_t>(total, value), extents_t{}, value);
}
TEST_CASE("fill_bytes handles 3D strided permutation layouts", "[fill_bytes][3d][stride][permutation]")
{
constexpr int dim0 = 25;
constexpr int dim1 = 37;
constexpr int dim2 = 41;
using extents_t = cuda::std::extents<int, dim0, dim1, dim2>;
constexpr int span = (dim0 - 1) + (dim1 - 1) * dim2 * dim0 + (dim2 - 1) * dim0 + 1;
cuda::std::array<int, 3> strides{1, dim2 * dim0, dim0};
auto input = make_host_data<uint32_t>(span, 0xCD);
constexpr auto value = pattern32::value;
auto expected = to_byte_vector(input);
for (int i = 0; i < dim0; ++i)
{
for (int j = 0; j < dim1; ++j)
{
for (int k = 0; k < dim2; ++k)
{
int offset = i + j * dim2 * dim0 + k * dim0;
fill_expected_element<uint32_t>(expected, offset, value);
}
}
}
test_impl_stride(input, expected, extents_t{}, strides, value);
}
TEST_CASE("fill_bytes handles 3D strided tile_size greater than one", "[fill_bytes][3d][stride][tile]")
{
constexpr int dim0 = 27;
constexpr int dim1 = 39;
constexpr int dim2 = 47;
using extents_t = cuda::std::extents<int, dim0, dim1, dim2>;
constexpr int stride0 = 64;
constexpr int stride1 = 2048;
constexpr int span_size = (dim0 - 1) * stride0 + (dim1 - 1) * stride1 + dim2;
cuda::std::array<int, 3> strides{stride0, stride1, 1};
auto input = make_host_data<uint32_t>(span_size, 0xCD);
constexpr auto value = pattern32::value;
auto expected = to_byte_vector(input);
for (int i = 0; i < dim0; ++i)
{
for (int j = 0; j < dim1; ++j)
{
for (int k = 0; k < dim2; ++k)
{
int offset = i * stride0 + j * stride1 + k;
fill_expected_element<uint32_t>(expected, offset, value);
}
}
}
test_impl_stride(input, expected, extents_t{}, strides, value);
}
TEST_CASE("fill_bytes preserves surrounding bytes in strided subviews with offsets", "[fill_bytes][stride][offset]")
{
constexpr int rows = 2;
constexpr int cols = 3;
constexpr int ld = 4;
constexpr int offset = 3;
constexpr int alloc = 16;
using extents_t = cuda::std::extents<int, rows, cols>;
cuda::std::array<int, 2> strides{1, ld};
auto input = make_host_data<uint32_t>(alloc, 0xCD);
constexpr auto value = uint32_t{0x12345678};
auto expected = to_byte_vector(input);
for (int row = 0; row < rows; ++row)
{
for (int col = 0; col < cols; ++col)
{
fill_expected_element<uint32_t>(expected, offset + row + col * ld, value);
}
}
test_impl_stride(input, expected, extents_t{}, strides, value, offset);
}
/***********************************************************************************************************************
* Edge Cases
**********************************************************************************************************************/
TEST_CASE("fill_bytes handles rank-zero and zero-size mdspans", "[fill_bytes][edge]")
{
// rank-zero
{
using extents_t = cuda::std::extents<int>;
auto input = make_host_data<uint32_t>(1, 0xCD);
auto value = pattern32::value;
test_impl(input, contiguous_fill_bytes<uint32_t>(1, value), extents_t{}, value);
}
// zero-size
{
auto input = make_host_data<uint32_t>(1, 0xCD);
test_impl(input, to_byte_vector(input), cuda::std::dims<1>{0}, uint32_t{0xdeadbeef});
}
}
TEST_CASE("fill_bytes rejects interleaved layout", "[fill_bytes][throw]")
{
using extents_t = cuda::std::extents<int, 2, 2>;
using mapping_t = cuda::layout_stride_relaxed::mapping<extents_t>;
auto input = make_host_data<uint32_t>(6, 0xCD);
thrust::device_vector<uint32_t> device_data(input.begin(), input.end());
cuda::device_mdspan<uint32_t, extents_t, cuda::layout_stride_relaxed> dst(
thrust::raw_pointer_cast(device_data.data()), mapping_t(extents_t{}, cuda::dstrides<int, 2>(2, 3)));
REQUIRE_THROWS_AS(cuda::experimental::fill_bytes(dst, uint32_t{0x12345678}, stream), std::invalid_argument);
}

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cccl_upstream/cudax/test/fill_bytes/fill_bytes_mdspan_example.cu
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//===----------------------------------------------------------------------===//
//
// Part of CUDA Experimental 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) 2026 NVIDIA CORPORATION & AFFILIATES.
//
//===----------------------------------------------------------------------===//
#include <thrust/device_vector.h>
#include <thrust/host_vector.h>
#include <cuda/mdspan>
#include <cuda/std/cstdint>
#include <cuda/stream>
#include <cuda/experimental/fill_bytes.cuh>
#include <cstring>
#include "testing.cuh"
TEST_CASE("fill_bytes mdspan documentation example", "[fill_bytes][example]")
{
// example-begin fill-bytes-mdspan
using extents_t = cuda::std::dims<2>;
extents_t extents{2, 3};
thrust::device_vector<int> device_data(extents.extent(0) * extents.extent(1));
int* dst_ptr = thrust::raw_pointer_cast(device_data.data());
cuda::device_mdspan<int, extents_t> dst(dst_ptr, extents);
cuda::stream stream{cuda::device_ref{0}};
cuda::experimental::fill_bytes(dst, uint32_t{0xFF00FF00}, stream);
// example-end fill-bytes-mdspan
stream.sync();
const thrust::host_vector<int> actual(device_data);
for (const int value : actual)
{
uint32_t value_bits{};
std::memcpy(&value_bits, &value, sizeof(value_bits));
REQUIRE(value_bits == uint32_t{0xFF00FF00});
}
}