Files
project_6/cccl_upstream/python/cuda_cccl/CMakeLists.txt
muh-bot 2a7ca101d7 feat(cccl): integrate missing CCCL directories — python/, ci/, .agent/, docs/, test/
Sparse-checkout from NVIDIA/cccl main branch to complete cccl_upstream:

Added:
- python/cuda_cccl/ (226 files) — Python bindings for device-level algorithms
  Critical for muh toolchain: cuda.compute.reduce_into, scan, radix_sort, etc.
  Includes 204 .py files with full test coverage for all 27 algorithms
- ci/ (163 files) — Build/test infrastructure
  build_cub.sh, test_cub.sh, build_and_test_targets.sh, matrix.yaml
  Directly maps to our [INFRA-CI] and [INFRA-BUILD] items
- .agent/skills/ (7 files) — NVIDIA's own agent skills for CCCL
  cccl-style/SKILL.md, cccl-test/SKILL.md, sass-diff/SKILL.md
- docs/ (491 files) — Official CCCL documentation
  CI references, CMake guides, Python compute docs, libcudacxx PTX docs
- test/ (12 files) — Top-level integration tests (cuda_smoke, stdpar)
- Root configs: .clang-format, .clang-tidy, CONTRIBUTING.md, pyproject.toml
- CLAUDE.md symlink → AGENTS.md (NVIDIA's standard)

cccl_upstream now mirrors full NVIDIA/cccl structure:
  Before: 42M (cub + thrust + libcudacxx + cudax + c + examples + benchmarks)
  After:  53M (+python +ci +docs +.agent +test +configs)

This completes the CCCL base needed for:
- [muh-bench] items: ci/util/build_and_test_targets.sh for targeted builds
- [CCCL-verify] items: python/cuda_cccl/tests/ as reference implementations
- [CCCL-test] items: ci/test_cub.sh, ci/test_thrust.sh
- Agent workflow: .agent/skills/ for consistent style and test patterns
2026-08-07 02:34:33 +00:00

188 lines
5.7 KiB
CMake

# Copyright (c) 2025, NVIDIA CORPORATION & AFFILIATES. ALL RIGHTS RESERVED.
#
# SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
cmake_minimum_required(VERSION 3.30)
# Must be set before project() initializes the CUDA language; otherwise CMake
# < 3.23 defaults to sm_52, which is below CCCL's minimum supported arch.
include(../../cmake/CCCLCheckCudaArchitectures.cmake)
set(
CMAKE_CUDA_ARCHITECTURES
"${minimum_cccl_arch}"
CACHE STRING
"CUDA architectures for CCCL"
)
project(cuda_cccl DESCRIPTION "Python package cuda_cccl" LANGUAGES CUDA CXX C)
find_package(CUDAToolkit REQUIRED)
set(CUDA_VERSION_MAJOR ${CUDAToolkit_VERSION_MAJOR})
set(CUDA_VERSION_DIR "cu${CUDA_VERSION_MAJOR}")
message(
STATUS
"Building for CUDA ${CUDA_VERSION_MAJOR}, output directory: ${CUDA_VERSION_DIR}"
)
# Build cuda_cccl against either cccl.c.parallel (v1, NVRTC) by default or
# cccl.c.parallel.v2 (HostJIT) when CCCL_PYTHON_USE_V2=ON. v2 is opt-in until
# it replaces v1 across the matrix.
set(_cccl_root ../..)
set(CCCL_TOPLEVEL_PROJECT ON) # Enable the developer builds
option(
CCCL_PYTHON_USE_V2
"Build cuda_cccl against cccl.c.parallel.v2 (HostJIT)."
OFF
)
if (CCCL_PYTHON_USE_V2)
set(CCCL_ENABLE_C_PARALLEL_V2 ON)
set(CCCL_C_PARALLEL_V2_LIBRARY_OUTPUT_DIRECTORY ${SKBUILD_PROJECT_NAME})
set(_cccl_c_parallel_target cccl.c.parallel.v2)
set(_using_v2_py "True")
else()
set(CCCL_ENABLE_C_PARALLEL ON)
set(CCCL_C_PARALLEL_LIBRARY_OUTPUT_DIRECTORY ${SKBUILD_PROJECT_NAME})
set(_cccl_c_parallel_target cccl.c.parallel)
set(_using_v2_py "False")
endif()
# Surface the v1/v2 choice to Python (tests use it to skip v2-only failures,
# and __init__.py uses it to wire up wheel-bundled hostjit header paths).
# Generated into the build dir and installed via CMake — writing into the
# source tree would miss scikit-build-core's package-file snapshot.
set(_build_info_py "${CMAKE_CURRENT_BINARY_DIR}/_build_info.py")
file(
WRITE "${_build_info_py}"
"# Auto-generated by CMakeLists.txt; do not edit.\nUSING_V2 = ${_using_v2_py}\n"
)
install(FILES "${_build_info_py}" DESTINATION cuda/compute)
# Just install the rest:
set(libcudacxx_ENABLE_INSTALL_RULES ON)
set(CUB_ENABLE_INSTALL_RULES ON)
set(Thrust_ENABLE_INSTALL_RULES ON)
# Install to our output location:
include(GNUInstallDirs)
set(old_libdir "${CMAKE_INSTALL_LIBDIR}") # push
set(old_includedir "${CMAKE_INSTALL_INCLUDEDIR}") # push
set(CMAKE_INSTALL_LIBDIR "cuda/cccl/headers/lib")
set(CMAKE_INSTALL_INCLUDEDIR "cuda/cccl/headers/include")
add_subdirectory(${_cccl_root} _parent_cccl)
set(CMAKE_INSTALL_LIBDIR "${old_libdir}") # pop
set(CMAKE_INSTALL_INCLUDEDIR "${old_includedir}") # pop
# Install version-specific binaries
set(_cccl_c_parallel_install_targets ${_cccl_c_parallel_target})
if (CCCL_PYTHON_USE_V2)
list(APPEND _cccl_c_parallel_install_targets libnvcc)
endif()
install(
TARGETS ${_cccl_c_parallel_install_targets}
DESTINATION cuda/compute/${CUDA_VERSION_DIR}/cccl
)
# Build and install Cython extension
find_package(Python3 COMPONENTS Interpreter Development.Module REQUIRED)
set(CYTHON_version_command "${Python3_EXECUTABLE}" -m cython --version)
execute_process(
COMMAND ${CYTHON_version_command}
OUTPUT_VARIABLE CYTHON_version_output
ERROR_VARIABLE CYTHON_version_output
OUTPUT_STRIP_TRAILING_WHITESPACE
ERROR_STRIP_TRAILING_WHITESPACE
COMMAND_ERROR_IS_FATAL ANY
)
if ("${CYTHON_version_output}" MATCHES "^[Cc]ython version ([^,]+)")
set(CYTHON_VERSION "${CMAKE_MATCH_1}")
else()
message(
FATAL_ERROR
"Failed to parse Cython version from:\n${CYTHON_version_output}"
)
endif()
# -3 generates source for Python 3
# -M generates depfile
# -t cythonizes if PYX is newer than preexisting output
# -w sets working directory
set(
CYTHON_FLAGS
-3
-M
-t
-w
"${cuda_cccl_SOURCE_DIR}"
)
message(STATUS "Using Cython ${CYTHON_VERSION}")
set(pyx_source_file "${cuda_cccl_SOURCE_DIR}/cuda/compute/_bindings_impl.pyx")
set(_generated_extension_src "${cuda_cccl_BINARY_DIR}/_bindings_impl.c")
set(_depfile "${cuda_cccl_BINARY_DIR}/_bindings_impl.c.dep")
# Backend-conditional Cython .pxi files. Where v1 and v2 expose different
# struct layouts or call signatures, the .pyx `include`s a generated .pxi
# whose source is chosen here. The helpers inside present a uniform interface
# so the rest of _bindings_impl.pyx stays backend-agnostic.
if (CCCL_PYTHON_USE_V2)
set(_backend_suffix "v2")
else()
set(_backend_suffix "v1")
endif()
foreach (
_pxi_stem
segmented_reduce_backend
binary_search_backend
op_code_type
serialization
)
configure_file(
"${CMAKE_CURRENT_SOURCE_DIR}/cuda/compute/_bindings_${_pxi_stem}_${_backend_suffix}.pxi"
"${CMAKE_CURRENT_BINARY_DIR}/_bindings_${_pxi_stem}.pxi"
COPYONLY
)
endforeach()
# Custom Cython compilation command. `-I ${BINARY_DIR}` lets the .pyx's
# `include "_bindings_..._backend.pxi"` resolve to the file we configured
# above.
add_custom_command(
OUTPUT "${_generated_extension_src}"
COMMAND
"${Python3_EXECUTABLE}" -m cython
# gersemi: off
${CYTHON_FLAGS}
-I "${CMAKE_CURRENT_BINARY_DIR}"
"${pyx_source_file}"
--output-file "${_generated_extension_src}"
# gersemi: on
DEPENDS "${pyx_source_file}"
DEPFILE "${_depfile}"
COMMENT "Cythonizing ${pyx_source_file} for CUDA ${CUDA_VERSION_MAJOR}"
)
add_custom_target(
cythonize_bindings_impl
ALL
DEPENDS "${_generated_extension_src}"
)
python3_add_library(
_bindings_impl
MODULE
WITH_SOABI
"${_generated_extension_src}"
)
add_dependencies(_bindings_impl cythonize_bindings_impl)
target_link_libraries(
_bindings_impl
PRIVATE #
${_cccl_c_parallel_target}
CUDA::cuda_driver
)
set_target_properties(_bindings_impl PROPERTIES INSTALL_RPATH "$ORIGIN/cccl")
install(TARGETS _bindings_impl DESTINATION cuda/compute/${CUDA_VERSION_DIR})