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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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478
cccl_upstream/cudax/include/cuda/experimental/__launch/launch.cuh
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@@ -1,478 +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.
//
//===----------------------------------------------------------------------===//
#ifndef _CUDAX__LAUNCH_LAUNCH
#define _CUDAX__LAUNCH_LAUNCH
#include <cuda/std/detail/__config>
#if defined(_CCCL_IMPLICIT_SYSTEM_HEADER_GCC)
# pragma GCC system_header
#elif defined(_CCCL_IMPLICIT_SYSTEM_HEADER_CLANG)
# pragma clang system_header
#elif defined(_CCCL_IMPLICIT_SYSTEM_HEADER_MSVC)
# pragma system_header
#endif // no system header
#include <cuda/__driver/driver_api.h>
#include <cuda/__launch/configuration.h>
#include <cuda/__launch/launch.h>
#include <cuda/__stream/launch_transform.h>
#include <cuda/__stream/stream_ref.h>
#include <cuda/hierarchy>
#include <cuda/std/__exception/cuda_error.h>
#include <cuda/std/__exception/exception_macros.h>
#include <cuda/std/__type_traits/is_function.h>
#include <cuda/std/__type_traits/is_pointer.h>
#include <cuda/std/__type_traits/type_identity.h>
#include <cuda/std/__utility/forward.h>
#include <cuda/std/__utility/pod_tuple.h>
#include <cuda/experimental/__execution/completion_signatures.cuh>
#include <cuda/experimental/__execution/cpos.cuh>
#include <cuda/experimental/__execution/visit.cuh>
#include <cuda/experimental/__graph/concepts.cuh>
#include <cuda/experimental/__graph/graph_node_ref.cuh>
#include <cuda/experimental/__graph/path_builder.cuh>
#include <cuda/experimental/__kernel/kernel_ref.cuh>
#include <cuda/experimental/__utility/ensure_current_device.cuh>
#include <cuda/std/__cccl/prologue.h>
_CCCL_BEGIN_NAMESPACE_CUDA
template <class... _Args>
[[nodiscard]] _CCCL_HOST_API ::CUfunction __get_cufunction_of(experimental::kernel_ref<void(_Args...)> __kernel)
{
return ::cuda::__driver::__kernelGetFunction(__kernel.get());
}
_CCCL_TEMPLATE(typename _GraphInserter)
_CCCL_REQUIRES(experimental::graph_inserter<_GraphInserter>)
_CCCL_HOST_API experimental::graph_node_ref
__do_launch(_GraphInserter&& __inserter, ::CUlaunchConfig& __config, ::CUfunction __kernel, void** __args_ptrs)
{
::CUDA_KERNEL_NODE_PARAMS __node_params{};
__node_params.func = __kernel;
__node_params.gridDimX = __config.gridDimX;
__node_params.gridDimY = __config.gridDimY;
__node_params.gridDimZ = __config.gridDimZ;
__node_params.blockDimX = __config.blockDimX;
__node_params.blockDimY = __config.blockDimY;
__node_params.blockDimZ = __config.blockDimZ;
__node_params.sharedMemBytes = __config.sharedMemBytes;
__node_params.kernelParams = __args_ptrs;
auto __dependencies = __inserter.get_dependencies();
const auto __node = ::cuda::__driver::__graphAddKernelNode(
__inserter.get_graph().get(), __dependencies.data(), __dependencies.size(), __node_params);
for (unsigned int __i = 0; __i < __config.numAttrs; ++__i)
{
::cuda::__driver::__graphKernelNodeSetAttribute(__node, __config.attrs[__i].id, __config.attrs[__i].value);
}
// TODO skip the update if called on rvalue?
__inserter.__clear_and_set_dependency_node(__node);
return experimental::graph_node_ref{__node, __inserter.get_graph().get()};
}
_CCCL_TEMPLATE(typename _GraphInserter)
_CCCL_REQUIRES(experimental::graph_inserter<_GraphInserter>)
_CCCL_HOST_API ::cuda::stream_ref __stream_or_invalid([[maybe_unused]] const _GraphInserter& __inserter)
{
return ::cuda::stream_ref{::cuda::invalid_stream};
}
_CCCL_TEMPLATE(typename _GraphInserter)
_CCCL_REQUIRES(experimental::graph_inserter<_GraphInserter>)
_CCCL_HOST_API _GraphInserter&& __forward_or_cast_to_stream_ref(_GraphInserter&& __inserter)
{
return ::cuda::std::forward<_GraphInserter>(__inserter);
}
_CCCL_END_NAMESPACE_CUDA
namespace cuda::experimental
{
template <typename... _ExpTypes, typename _Dst, typename _Config>
_CCCL_HOST_API auto __launch_impl(_Dst&& __dst, _Config __conf, ::CUfunction __kernel, _ExpTypes... __args)
{
static_assert(!::cuda::std::is_same_v<decltype(__conf.hierarchy()), no_init_t>,
"Can't launch a configuration without hierarchy dimensions");
using _Hierarchy = typename _Config::hierarchy_type;
::CUlaunchConfig __config{};
constexpr bool __has_cluster_level = _Hierarchy::has_level(cluster);
constexpr unsigned int __num_attrs_needed =
::cuda::__detail::kernel_config_count_attr_space(__conf) + __has_cluster_level;
::CUlaunchAttribute __attrs[__num_attrs_needed == 0 ? 1 : __num_attrs_needed];
__config.attrs = &__attrs[0];
__config.numAttrs = 0;
::cudaError_t __status = cuda::__detail::apply_kernel_config(__conf, __config, __kernel);
if (__status != ::cudaSuccess)
{
_CCCL_THROW(::cuda::cuda_error, __status, "Failed to prepare a launch configuration");
}
__config.gridDimX = block.dims(grid, __conf).x;
__config.gridDimY = block.dims(grid, __conf).y;
__config.gridDimZ = block.dims(grid, __conf).z;
__config.blockDimX = gpu_thread.dims(block, __conf).x;
__config.blockDimY = gpu_thread.dims(block, __conf).y;
__config.blockDimZ = gpu_thread.dims(block, __conf).z;
if constexpr (__has_cluster_level)
{
::CUlaunchAttribute __cluster_dims_attr{};
__cluster_dims_attr.id = ::CU_LAUNCH_ATTRIBUTE_CLUSTER_DIMENSION;
__cluster_dims_attr.value.clusterDim.x = block.dims(cluster, __conf).x;
__cluster_dims_attr.value.clusterDim.y = block.dims(cluster, __conf).y;
__cluster_dims_attr.value.clusterDim.z = block.dims(cluster, __conf).z;
__config.attrs[__config.numAttrs++] = __cluster_dims_attr;
}
const void* __pArgs[(sizeof...(__args) > 0) ? sizeof...(__args) : 1]{::cuda::std::addressof(__args)...};
return ::cuda::__do_launch(::cuda::std::forward<_Dst>(__dst), __config, __kernel, const_cast<void**>(__pArgs));
}
template <typename _Submitter>
_CCCL_CONCEPT work_submitter =
graph_inserter<_Submitter> || ::cuda::std::is_convertible_v<_Submitter, ::cuda::stream_ref>;
//! @brief Launch a kernel functor with specified configuration and arguments
//!
//! Launches a kernel functor object on the specified stream and with specified
//! configuration. Kernel functor object is a type with __device__ operator().
//! Functor might or might not accept the configuration as its first argument.
//!
//! @par Snippet
//! @code
//! #include <cstdio>
//! #include <cuda/experimental/launch.cuh>
//!
//! struct kernel {
//! template <typename Configuration>
//! __device__ void operator()(Configuration conf, unsigned int
//! thread_to_print) {
//! if (conf.hierarchy().rank(cudax::thread, cudax::grid) == thread_to_print) {
//! printf("Hello from the GPU\n");
//! }
//! }
//! };
//!
//! void launch_kernel(cuda::stream_ref stream) {
//! auto dims = cudax::make_hierarchy(cudax::block_dims<128>(),
//! cudax::grid_dims(4)); auto config = cudax::make_config(dims,
//! cudax::launch_cooperative());
//!
//! cudax::launch(stream, config, kernel(), 42);
//! }
//! @endcode
//!
//! @param __submitter
//! cuda::stream_ref to launch the kernel into
//!
//! @param __conf
//! configuration for this launch
//!
//! @param __kernel
//! kernel functor to be launched
//!
//! @param __args
//! arguments to be passed into the kernel functor
_CCCL_TEMPLATE(typename... _Args, typename... _Config, typename _Submitter, typename _Dimensions, typename _Kernel)
_CCCL_REQUIRES(work_submitter<_Submitter> _CCCL_AND(!::cuda::std::is_pointer_v<_Kernel>)
_CCCL_AND(!::cuda::std::is_function_v<_Kernel>) _CCCL_AND(!__detail::__is_kernel_ref_v<_Kernel>))
_CCCL_HOST_API auto launch(_Submitter&& __submitter,
const kernel_config<_Dimensions, _Config...>& __conf,
const _Kernel& __kernel,
_Args&&... __args)
{
__ensure_current_device __dev_setter{__submitter};
auto __combined = __conf.combine_with_default(__kernel);
auto __launcher = ::cuda::__get_kernel_launcher<_Kernel,
decltype(__combined),
::cuda::std::decay_t<transformed_device_argument_t<_Args>>...>();
return ::cuda::experimental::__launch_impl(
::cuda::__forward_or_cast_to_stream_ref<_Submitter>(::cuda::std::forward<_Submitter>(__submitter)),
__combined,
::cuda::__get_cufunction_of(__launcher),
__combined,
__kernel,
launch_transform(::cuda::__stream_or_invalid(__submitter), ::cuda::std::forward<_Args>(__args))...);
}
//! @brief Launch a kernel function with specified configuration and arguments
//!
//! Launches a kernel function on the specified stream and with specified
//! configuration. Kernel function is a function with __global__ annotation.
//! Function might or might not accept the configuration as its first argument.
//!
//! @par Snippet
//! @code
//! #include <cstdio>
//! #include <cuda/experimental/launch.cuh>
//!
//! template <typename Configuration>
//! __global__ void kernel(Configuration conf, unsigned int thread_to_print) {
//! if (conf.dims.rank(cudax::thread, cudax::grid) == thread_to_print) {
//! printf("Hello from the GPU\n");
//! }
//! }
//!
//! void launch_kernel(cuda::stream_ref stream) {
//! auto dims = cudax::make_hierarchy(cudax::block_dims<128>(),
//! cudax::grid_dims(4)); auto config = cudax::make_config(dims,
//! cudax::launch_cooperative());
//!
//! cudax::launch(stream, config, kernel<decltype(config)>, 42);
//! }
//! @endcode
//!
//! @param __submitter
//! cuda::stream_ref to launch the kernel into
//!
//! @param __conf
//! configuration for this launch
//!
//! @param __kernel
//! kernel function to be launched
//!
//! @param __args
//! arguments to be passed into the kernel function
//!
_CCCL_TEMPLATE(
typename... _ExpArgs, typename... _ActArgs, typename _Submitter, typename... _Config, typename _Dimensions)
_CCCL_REQUIRES(work_submitter<_Submitter> _CCCL_AND(sizeof...(_ExpArgs) == sizeof...(_ActArgs)))
_CCCL_HOST_API auto launch(_Submitter&& __submitter,
const kernel_config<_Dimensions, _Config...>& __conf,
void (*__kernel)(kernel_config<_Dimensions, _Config...>, _ExpArgs...),
_ActArgs&&... __args)
{
__ensure_current_device __dev_setter{__submitter};
return ::cuda::experimental::__launch_impl<kernel_config<_Dimensions, _Config...>, _ExpArgs...>(
::cuda::__forward_or_cast_to_stream_ref<_Submitter>(__submitter), //
__conf,
::cuda::__get_cufunction_of(reinterpret_cast<const void*>(__kernel)),
__conf,
launch_transform(::cuda::__stream_or_invalid(__submitter), ::cuda::std::forward<_ActArgs>(__args))...);
}
//! @brief Launch a kernel with specified configuration and arguments
//!
//! Launches a kernel on the specified stream and with specified configuration.
//! Kernel might or might not accept the configuration as its first argument.
//!
//! @par Snippet
//! @code
//! #include <cstdio>
//! #include <cuda/experimental/launch.cuh>
//!
//! template <typename Configuration>
//! __global__ void kernel(Configuration conf, unsigned int thread_to_print) {
//! if (conf.hierarchy().rank(cudax::thread, cudax::grid) == thread_to_print) {
//! printf("Hello from the GPU\n");
//! }
//! }
//!
//! void launch_kernel(cuda::stream_ref stream) {
//! auto dims = cudax::make_hierarchy(cudax::block_dims<128>(),
//! cudax::grid_dims(4)); auto config = cudax::make_config(dims,
//! cudax::launch_cooperative());
//!
//! cudax::launch(stream, config,
//! cudax::kernel_ref{kernel<decltype(config)}>, 42);
//! }
//! @endcode
//!
//! @param __submitter
//! cuda::stream_ref to launch the kernel into
//!
//! @param __conf
//! configuration for this launch
//!
//! @param __kernel
//! kernel to be launched
//!
//! @param __args
//! arguments to be passed into the kernel
//!
_CCCL_TEMPLATE(
typename... _ExpArgs, typename... _ActArgs, typename _Submitter, typename... _Config, typename _Dimensions)
_CCCL_REQUIRES(work_submitter<_Submitter> _CCCL_AND(sizeof...(_ExpArgs) == sizeof...(_ActArgs)))
_CCCL_HOST_API auto launch(_Submitter&& __submitter,
const kernel_config<_Dimensions, _Config...>& __conf,
kernel_ref<void(kernel_config<_Dimensions, _Config...>, _ExpArgs...)> __kernel,
_ActArgs&&... __args)
{
__ensure_current_device __dev_setter{__submitter};
return ::cuda::experimental::__launch_impl<kernel_config<_Dimensions, _Config...>, _ExpArgs...>(
::cuda::__forward_or_cast_to_stream_ref<_Submitter>(__submitter), //
__conf,
::cuda::__get_cufunction_of(__kernel),
__conf,
launch_transform(::cuda::__stream_or_invalid(__submitter), ::cuda::std::forward<_ActArgs>(__args))...);
}
//! @brief Launch a kernel function with specified configuration and arguments
//!
//! Launches a kernel function on the specified stream and with specified
//! configuration. Kernel function is a function with __global__ annotation.
//! Function might or might not accept the configuration as its first argument.
//!
//! @par Snippet
//! @code
//! #include <cstdio>
//! #include <cuda/experimental/launch.cuh>
//!
//! template <typename Configuration>
//! __global__ void kernel(Configuration conf, unsigned int thread_to_print) {
//! if (conf.hierarchy().rank(cudax::thread, cudax::grid) == thread_to_print) {
//! printf("Hello from the GPU\n");
//! }
//! }
//!
//! void launch_kernel(cuda::stream_ref stream) {
//! auto dims = cudax::make_hierarchy(cudax::block_dims<128>(),
//! cudax::grid_dims(4)); auto config = cudax::make_config(dims,
//! cudax::launch_cooperative());
//!
//! cudax::launch(stream, config, kernel<decltype(config)>, 42);
//! }
//! @endcode
//!
//! @param __submitter
//! cuda::stream_ref to launch the kernel into
//!
//! @param __conf
//! configuration for this launch
//!
//! @param __kernel
//! kernel function to be launched
//!
//! @param __args
//! arguments to be passed into the kernel function
_CCCL_TEMPLATE(
typename... _ExpArgs, typename... _ActArgs, typename _Submitter, typename... _Config, typename _Dimensions)
_CCCL_REQUIRES(work_submitter<_Submitter> _CCCL_AND(sizeof...(_ExpArgs) == sizeof...(_ActArgs)))
_CCCL_HOST_API auto launch(_Submitter&& __submitter,
const kernel_config<_Dimensions, _Config...>& __conf,
void (*__kernel)(_ExpArgs...),
_ActArgs&&... __args)
{
__ensure_current_device __dev_setter{__submitter};
return ::cuda::experimental::__launch_impl<_ExpArgs...>(
::cuda::__forward_or_cast_to_stream_ref<_Submitter>(::cuda::std::forward<_Submitter>(__submitter)), //
__conf,
::cuda::__get_cufunction_of(reinterpret_cast<const void*>(__kernel)),
launch_transform(::cuda::__stream_or_invalid(__submitter), ::cuda::std::forward<_ActArgs>(__args))...);
}
//! @brief Launch a kernel with specified configuration and arguments
//!
//! Launches a kernel on the specified stream and with specified configuration.
//! Kernel might or might not accept the configuration as its first argument.
//!
//! @par Snippet
//! @code
//! #include <cstdio>
//! #include <cuda/experimental/launch.cuh>
//!
//! template <typename Configuration>
//! __global__ void kernel(Configuration conf, unsigned int thread_to_print) {
//! if (conf.hierarchy().rank(cudax::thread, cudax::grid) == thread_to_print) {
//! printf("Hello from the GPU\n");
//! }
//! }
//!
//! void launch_kernel(cuda::stream_ref stream) {
//! auto dims = cudax::make_hierarchy(cudax::block_dims<128>(),
//! cudax::grid_dims(4)); auto config = cudax::make_config(dims,
//! cudax::launch_cooperative());
//!
//! cudax::launch(stream, config,
//! cudax::kernel_ref{kernel<decltype(config)>}, 42);
//! }
//! @endcode
//!
//! @param __submitter
//! cuda::stream_ref to launch the kernel into
//!
//! @param __conf
//! configuration for this launch
//!
//! @param __kernel
//! kernel to be launched
//!
//! @param __args
//! arguments to be passed into the kernel
_CCCL_TEMPLATE(
typename... _ExpArgs, typename... _ActArgs, typename _Submitter, typename... _Config, typename _Dimensions)
_CCCL_REQUIRES(work_submitter<_Submitter> _CCCL_AND(sizeof...(_ExpArgs) == sizeof...(_ActArgs)))
_CCCL_HOST_API auto launch(_Submitter&& __submitter,
const kernel_config<_Dimensions, _Config...>& __conf,
kernel_ref<void(_ExpArgs...)> __kernel,
_ActArgs&&... __args)
{
__ensure_current_device __dev_setter{__submitter};
return ::cuda::experimental::__launch_impl<_ExpArgs...>(
::cuda::__forward_or_cast_to_stream_ref<_Submitter>(::cuda::std::forward<_Submitter>(__submitter)), //
__conf,
::cuda::__get_cufunction_of(__kernel),
launch_transform(::cuda::__stream_or_invalid(__submitter), ::cuda::std::forward<_ActArgs>(__args))...);
}
//
// Lazy launch
//
struct _CCCL_TYPE_VISIBILITY_DEFAULT __kernel_t
{
template <class _Config, class _Fn, class... _Args>
struct _CCCL_TYPE_VISIBILITY_DEFAULT __sndr_t;
};
template <class _Config, class _Fn, class... _Args>
struct _CCCL_TYPE_VISIBILITY_DEFAULT __kernel_t::__sndr_t
{
using sender_concept = execution::sender_t;
template <class _Self>
_CCCL_HOST_DEVICE_API static constexpr auto get_completion_signatures() noexcept
{
return execution::completion_signatures<execution::set_value_t(), execution::set_error_t(cudaError_t)>();
}
_CCCL_NO_UNIQUE_ADDRESS __kernel_t __tag_{};
::cuda::std::__tuple<_Config, _Fn, _Args...> __args_;
};
template <class _Dimensions, class... _Config, class _Fn, class... _Args>
_CCCL_HOST_DEVICE_API constexpr auto launch(kernel_config<_Dimensions, _Config...> __config, _Fn __fn, _Args... __args)
-> __kernel_t::__sndr_t<kernel_config<_Dimensions, _Config...>, _Fn, _Args...>
{
return {{}, {_CCCL_MOVE(__config), _CCCL_MOVE(__fn), _CCCL_MOVE(__args)...}};
}
// Hide from Doxygen — uses internal __kernel_t::__sndr_t types excluded by EXCLUDE_SYMBOLS.
#ifndef _CCCL_DOXYGEN_INVOKED
namespace execution
{
template <class _Config, class _Fn, class... _Args>
inline constexpr int structured_binding_size<__kernel_t::__sndr_t<_Config, _Fn, _Args...>> = 2;
} // namespace execution
#endif // !_CCCL_DOXYGEN_INVOKED
} // namespace cuda::experimental
#include <cuda/std/__cccl/epilogue.h>
#endif // _CUDAX__LAUNCH_LAUNCH

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cccl_upstream/cudax/include/cuda/experimental/__launch/param_kind.cuh
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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) 2025 NVIDIA CORPORATION & AFFILIATES.
//
//===----------------------------------------------------------------------===//
#ifndef _CUDAX__LAUNCH_PARAM_KIND_CUH
#define _CUDAX__LAUNCH_PARAM_KIND_CUH
#include <cuda/__cccl_config>
#if defined(_CCCL_IMPLICIT_SYSTEM_HEADER_GCC)
# pragma GCC system_header
#elif defined(_CCCL_IMPLICIT_SYSTEM_HEADER_CLANG)
# pragma clang system_header
#elif defined(_CCCL_IMPLICIT_SYSTEM_HEADER_MSVC)
# pragma system_header
#endif // no system header
#include <cuda/std/__type_traits/maybe_const.h>
#include <cuda/experimental/__detail/utility.cuh>
#include <cuda/std/__cccl/prologue.h>
namespace cuda::experimental
{
namespace __detail
{
enum class __param_kind : unsigned
{
_in = 1,
_out = 2,
_inout = 3
};
[[nodiscard]] _CCCL_HOST_DEVICE inline constexpr __param_kind operator&(__param_kind __a, __param_kind __b) noexcept
{
return __param_kind(unsigned(__a) & unsigned(__b));
}
template <typename _Ty, __param_kind _Kind>
struct [[nodiscard]] __box
{
::cuda::std::__maybe_const<_Kind == __param_kind::_in, _Ty>& __val;
};
struct __in_t
{
template <class _Ty>
__box<_Ty, __param_kind::_in> operator()(const _Ty& __v) const noexcept
{
return {__v};
}
};
struct __out_t
{
template <class _Ty>
__box<_Ty, __param_kind::_out> operator()(_Ty& __v) const noexcept
{
return {__v};
}
};
struct __inout_t
{
template <class _Ty>
__box<_Ty, __param_kind::_inout> operator()(_Ty& __v) const noexcept
{
return {__v};
}
};
} // namespace __detail
_CCCL_GLOBAL_CONSTANT __detail::__in_t in{};
_CCCL_GLOBAL_CONSTANT __detail::__out_t out{};
_CCCL_GLOBAL_CONSTANT __detail::__inout_t inout{};
} // namespace cuda::experimental
#include <cuda/std/__cccl/epilogue.h>
#endif // _CUDAX__LAUNCH_PARAM_KIND_CUH