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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

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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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396
cccl_upstream/cudax/test/launch/launch_smoke.cu
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@@ -1,396 +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) 2025 NVIDIA CORPORATION & AFFILIATES.
//
//===----------------------------------------------------------------------===//
// clang does not support __managed__ declarations, so clang-tidy produces spurious
// errors. https://github.com/llvm/llvm-project/pull/149716 seemingly adds support for
// __managed__ variables, but that PR seems to have stagnated.
#ifndef _CCCL_CLANG_TIDY_INVOKED
# include <cuda/atomic>
# include <cuda/memory>
# include <cuda/experimental/graph.cuh>
# include <cuda/experimental/kernel.cuh>
# include <cuda/experimental/launch.cuh>
# include <cuda/experimental/stream.cuh>
# include <cooperative_groups.h>
# include <testing.cuh>
__managed__ bool kernel_run_proof = false;
void check_kernel_run(cudaStream_t stream)
{
REQUIRE_CUDART(cudaStreamSynchronize(stream));
CHECK(kernel_run_proof);
kernel_run_proof = false;
}
struct kernel_run_proof_check
{
__device__ void operator()()
{
CHECK(kernel_run_proof);
kernel_run_proof = false;
}
};
void check_kernel_run(cudax::path_builder& pb)
{
cudax::launch(pb, cuda::make_config(cuda::block_dims<1>, cuda::grid_dims<1>), kernel_run_proof_check{});
}
struct functor_int_argument
{
__device__ void operator()(int dummy)
{
kernel_run_proof = true;
}
};
template <unsigned int BlockSize>
struct functor_taking_config
{
template <typename Config>
__device__ void operator()(Config config, int grid_size)
{
static_assert(cuda::gpu_thread.count(cuda::block, config) == BlockSize);
REQUIRE(cuda::block.count(cuda::grid, config) == grid_size);
kernel_run_proof = true;
}
};
__global__ void kernel_no_arguments()
{
kernel_run_proof = true;
}
__global__ void kernel_int_argument(int dummy)
{
kernel_run_proof = true;
}
template <typename Config, unsigned int BlockSize>
__global__ void kernel_taking_config(Config config, int grid_size)
{
functor_taking_config<BlockSize>()(config, grid_size);
}
struct my_dynamic_smem_t
{
int i;
};
template <typename SmemType>
struct dynamic_smem_single
{
template <typename Config>
__device__ void operator()(Config config)
{
decltype(auto) dynamic_smem = cuda::dynamic_shared_memory(config);
static_assert(::cuda::std::is_same_v<SmemType&, decltype(dynamic_smem)>);
REQUIRE(::cuda::device::is_object_from(dynamic_smem, ::cuda::device::address_space::shared));
kernel_run_proof = true;
}
};
template <typename SmemType, size_t Extent>
struct dynamic_smem_span
{
template <typename Config>
__device__ void operator()(Config config, int size)
{
auto dynamic_smem = cuda::dynamic_shared_memory(config);
static_assert(decltype(dynamic_smem)::extent == Extent);
static_assert(::cuda::std::is_same_v<SmemType&, decltype(dynamic_smem[1])>);
REQUIRE(dynamic_smem.size() == size);
REQUIRE(::cuda::device::is_object_from(dynamic_smem[1], ::cuda::device::address_space::shared));
kernel_run_proof = true;
}
};
struct launch_transform_to_int_convertible
{
int value_;
struct int_convertible
{
cudaStream_t stream_;
int value_;
int_convertible(cudaStream_t stream, int value) noexcept
: stream_(stream)
, value_(value)
{
// Check that the constructor runs before the kernel is launched
// Disabled for now because we don't handle it with graphs
// CHECK_FALSE(kernel_run_proof);
}
// Immovable to ensure that launch_transform doesn't copy the returned
// object
int_convertible(int_convertible&&) noexcept = delete;
~int_convertible() noexcept
{
// Check that the destructor runs after the kernel is launched
// Disabled for now because we don't handle it with graphs
// REQUIRE_CUDART(cudaStreamSynchronize(stream_));
// CHECK(kernel_run_proof);
}
// This is the value that will be passed to the kernel
int transformed_argument() const
{
return value_;
}
};
[[nodiscard]] friend int_convertible
transform_launch_argument(::cuda::stream_ref stream, launch_transform_to_int_convertible self) noexcept
{
return int_convertible(stream.get(), self.value_);
}
};
// Needs a separate function for Windows extended lambda
template <typename StreamOrPathBuilder>
void launch_smoke_test(StreamOrPathBuilder& dst)
{
cudax::__ensure_current_device guard(cuda::device_ref{0});
// Use raw stream to make sure it can be implicitly converted on call to launch
cudaStream_t stream;
REQUIRE_CUDART(cudaStreamCreate(&stream));
// Spell out all overloads to make sure they compile, include a check for implicit conversions
{
const int grid_size = 4;
constexpr int block_size = 256;
auto dimensions = cuda::make_hierarchy(cuda::grid_dims(grid_size), cuda::block_dims<256>());
auto config = cuda::make_config(dimensions);
// Not taking dims
{
cudax::launch(dst, config, kernel_no_arguments);
check_kernel_run(dst);
const int dummy = 1;
cudax::launch(dst, config, kernel_int_argument, dummy);
check_kernel_run(dst);
cudax::launch(dst, config, kernel_int_argument, 1);
check_kernel_run(dst);
cudax::launch(dst, config, kernel_int_argument, launch_transform_to_int_convertible{1});
check_kernel_run(dst);
cudax::launch(dst, config, kernel_int_argument, 1U);
check_kernel_run(dst);
# if _CCCL_CTK_AT_LEAST(12, 1)
cudax::launch(dst, config, cudax::kernel_ref{kernel_int_argument}, dummy);
check_kernel_run(dst);
cudax::launch(dst, config, cudax::kernel_ref{kernel_int_argument}, 1);
check_kernel_run(dst);
cudax::launch(dst, config, cudax::kernel_ref{kernel_int_argument}, launch_transform_to_int_convertible{1});
check_kernel_run(dst);
cudax::launch(dst, config, cudax::kernel_ref{kernel_int_argument}, 1U);
check_kernel_run(dst);
# endif // _CCCL_CTK_AT_LEAST(12, 1)
cudax::launch(dst, config, functor_int_argument(), dummy);
check_kernel_run(dst);
cudax::launch(dst, config, functor_int_argument(), 1);
check_kernel_run(dst);
cudax::launch(dst, config, functor_int_argument(), launch_transform_to_int_convertible{1});
check_kernel_run(dst);
cudax::launch(dst, config, functor_int_argument(), 1U);
check_kernel_run(dst);
}
// Config argument
{
auto functor_instance = functor_taking_config<block_size>();
auto kernel_instance = kernel_taking_config<decltype(config), block_size>;
# if _CCCL_CTK_AT_LEAST(12, 1)
cudax::kernel_ref kernel_ref_instance = kernel_instance;
# endif // _CCCL_CTK_AT_LEAST(12, 1)
cudax::launch(dst, config, functor_instance, grid_size);
check_kernel_run(dst);
cudax::launch(dst, config, functor_instance, ::cuda::std::move(grid_size));
check_kernel_run(dst);
cudax::launch(dst, config, functor_instance, launch_transform_to_int_convertible{grid_size});
check_kernel_run(dst);
cudax::launch(dst, config, functor_instance, static_cast<unsigned int>(grid_size));
check_kernel_run(dst);
cudax::launch(dst, config, kernel_instance, grid_size);
check_kernel_run(dst);
cudax::launch(dst, config, kernel_instance, ::cuda::std::move(grid_size));
check_kernel_run(dst);
cudax::launch(dst, config, kernel_instance, launch_transform_to_int_convertible{grid_size});
check_kernel_run(dst);
cudax::launch(dst, config, kernel_instance, static_cast<unsigned int>(grid_size));
check_kernel_run(dst);
# if _CCCL_CTK_AT_LEAST(12, 1)
cudax::launch(dst, config, kernel_ref_instance, grid_size);
check_kernel_run(dst);
cudax::launch(dst, config, kernel_ref_instance, ::cuda::std::move(grid_size));
check_kernel_run(dst);
cudax::launch(dst, config, kernel_ref_instance, launch_transform_to_int_convertible{grid_size});
check_kernel_run(dst);
cudax::launch(dst, config, kernel_ref_instance, static_cast<unsigned int>(grid_size));
check_kernel_run(dst);
# endif // _CCCL_CTK_AT_LEAST(12, 1)
}
}
// Lambda
{
cudax::launch(dst, cuda::block_dims<256>() & cuda::grid_dims(1), [] __device__() {
if (cuda::gpu_thread.rank(cuda::block) == 0)
{
printf("Hello from the GPU\n");
kernel_run_proof = true;
}
});
check_kernel_run(dst);
}
// Dynamic shared memory option
{
auto config = cuda::block_dims<32>() & cuda::grid_dims<1>();
auto test = [&](const auto& input_config) {
// Single element
{
auto config = input_config.add(cuda::dynamic_shared_memory<my_dynamic_smem_t>());
cudax::launch(dst, config, dynamic_smem_single<my_dynamic_smem_t>());
check_kernel_run(dst);
}
// Dynamic span
{
const int size = 2;
auto config = input_config.add(cuda::dynamic_shared_memory<my_dynamic_smem_t[]>(size));
cudax::launch(dst, config, dynamic_smem_span<my_dynamic_smem_t, ::cuda::std::dynamic_extent>(), size);
check_kernel_run(dst);
}
// Static span
{
constexpr int size = 3;
auto config = input_config.add(cuda::dynamic_shared_memory<my_dynamic_smem_t[size]>());
cudax::launch(dst, config, dynamic_smem_span<my_dynamic_smem_t, size>(), size);
check_kernel_run(dst);
}
};
test(config);
test(config.add(cuda::cooperative_launch(), cuda::launch_priority(0)));
}
}
C2H_TEST("Launch smoke stream", "[launch]")
{
// Use raw stream to make sure it can be implicitly converted on call to launch
cudaStream_t stream;
REQUIRE_CUDART(cudaStreamCreate(&stream));
launch_smoke_test(stream);
REQUIRE_CUDART(cudaStreamSynchronize(stream));
REQUIRE_CUDART(cudaStreamDestroy(stream));
}
C2H_TEST("Launch smoke path builder", "[launch]")
{
// Use raw stream to make sure it can be implicitly converted on call to launch
cudax::graph_builder g;
cudax::path_builder pb = cudax::start_path(g);
launch_smoke_test(pb);
// In CUDA 12.0 we don't test kernel_ref launches, so the node count is lower
# if _CCCL_CTK_BELOW(12, 1)
REQUIRE(g.node_count() == 48);
# else // ^^^ _CCCL_CTK_BELOW(12, 1) ^^^ / vvv _CCCL_CTK_AT_LEAST(12, 1) vvv
REQUIRE(g.node_count() == 64);
# endif // _CCCL_CTK_BELOW(12, 1)
auto exec = g.instantiate();
cudax::stream s{cuda::device_ref{0}};
exec.launch(s);
s.sync();
}
template <typename DefaultConfig>
struct kernel_with_default_config
{
DefaultConfig config;
kernel_with_default_config(DefaultConfig c)
: config(c)
{}
DefaultConfig default_config() const
{
return config;
}
template <typename Config, typename ConfigCheckFn>
__device__ void operator()(Config config, ConfigCheckFn check_fn)
{
check_fn(config);
}
};
void test_default_config()
{
cudax::stream stream{cuda::device_ref{0}};
auto grid = cuda::grid_dims(4);
auto block = cuda::block_dims<256>;
auto verify_lambda = [] __device__(auto config) {
static_assert(cuda::gpu_thread.count(cuda::block, config) == 256);
REQUIRE(cuda::block.count(cuda::grid, config) == 4);
cooperative_groups::this_grid().sync();
};
SECTION("Combine with empty")
{
kernel_with_default_config kernel{cuda::make_config(block, grid, cuda::cooperative_launch())};
static_assert(cuda::__is_kernel_config<decltype(kernel.default_config())>);
static_assert(cuda::__kernel_has_default_config<decltype(kernel)>);
cudax::launch(stream, cuda::make_config(), kernel, verify_lambda);
stream.sync();
}
SECTION("Combine with no overlap")
{
kernel_with_default_config kernel{cuda::make_config(block)};
cudax::launch(stream, cuda::make_config(grid, cuda::cooperative_launch()), kernel, verify_lambda);
stream.sync();
}
SECTION("Combine with overlap")
{
kernel_with_default_config kernel{cuda::make_config(cuda::block_dims<1>, cuda::cooperative_launch())};
cudax::launch(stream, cuda::make_config(block, grid, cuda::cooperative_launch()), kernel, verify_lambda);
stream.sync();
}
}
C2H_TEST("Launch with default config", "")
{
test_default_config();
}
#endif // _CCCL_CLANG_TIDY_INVOKED