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 rapids-cmake

NOTE: For the latest stable README.md ensure you are on the main branch.

Overview

This is a collection of CMake modules that are useful for all CUDA RAPIDS projects. By sharing the code in a single place it makes rolling out CMake fixes easier.

Installation

The rapids-cmake module is designed to be acquired via CMake's Fetch Content into your project.

cmake_minimum_required(...)

if(NOT EXISTS ${CMAKE_CURRENT_BINARY_DIR}/<PROJECT>_RAPIDS.cmake)
  file(DOWNLOAD https://raw.githubusercontent.com/rapidsai/rapids-cmake/branch-<VERSION_MAJOR>.<VERSION_MINOR>/RAPIDS.cmake
    ${CMAKE_CURRENT_BINARY_DIR}/<PROJECT>_RAPIDS.cmake)
endif()
include(${CMAKE_CURRENT_BINARY_DIR}/<PROJECT>_RAPIDS.cmake)

include(rapids-cmake)
include(rapids-cpm)
include(rapids-cuda)
include(rapids-export)
include(rapids-find)

project(....)

Note that we recommend you install rapids-cmake into the root CMakeLists.txt of your project before the first project call. This allows us to offer features such as rapids_cuda_architectures()

Usage

rapids-cmake provides a collection of useful CMake settings that any RAPIDS project may use. While they maybe common, we know that they aren't universal and might need to be composed in different ways.

To use function provided by rapids-cmake projects have two options:

  • Call include(rapids-<component>) as that imports all commonly used functions for that component
  • Load each function independently via include(${rapids-cmake-dir}/<component>/<function_name>.cmake)

Components

Complete online documentation for all components can be found at:

https://docs.rapids.ai/api/rapids-cmake/nightly/api.html

cmake

The rapids-cmake module contains helpful general CMake functionality

  • rapids_cmake_build_type( ) handles initialization of CMAKE_BUILD_TYPE
  • rapids_cmake_support_conda_env( target [MODIFY_PREFIX_PATH]) Establish a target that holds the CONDA environment include and link directories.
  • rapids_cmake_write_version_file( <file> ) Write a C++ header with a projects MAJOR, MINOR, and PATCH defines

cpm

The rapids-cpm module contains CPM functionality to allow projects to acquire dependencies consistently. For consistentcy All targets brought in via rapids-cpm are GLOBAL targets.

  • rapids_cpm_init() handles initialization of the CPM module.
  • raipds_cpm_find(<project> name BUILD_EXPORT_SET <name> INSTALL_EXPORT_SET <name>) Will search for a module and fall back to installing via CPM. Offers support to track dependencies for easy package exporting

cuda

The rapids-cuda module contains core functionality to allow projects to build CUDA code robustly. The most commonly used function are:

  • rapids_cuda_init_architectures(<project_name>) handles initialization of CMAKE_CUDA_ARCHITECTURE. MUST BE CALLED BEFORE PROJECT()
  • rapids_cuda_init_runtime(<mode>) handles initialization of CMAKE_CUDA_RUNTIME_LIBRARY.
  • rapids_cuda_patch_toolkit() corrects bugs in the CUDAToolkit module that are being upstreamed.

cython

The rapids_cython functions allow projects to easily build cython modules using scikit-build.

  • rapids_cython_init() handles initialization of scikit-build and cython.
  • rapids_create_modules([CXX] [SOURCE_FILES <src1> <src2> ...] [LINKED_LIBRARIES <lib1> <lib2> ... ] [INSTALL_DIR <install_path>] [MODULE_PREFIX <module_prefix>] ) will create cython modules for each provided source file

export

The rapids-export module contains core functionality to allow projects to easily record and write out build and install dependencies, that come from find_package or cpm

  • rapids_export(<type> <project> EXPORT_SET <name>) write out all the require components of a projects config module so that the install or build directory can be imported via find_package. See rapids_export documentation for full documentation

find

The rapids-find module contains core functionality to allow projects to easily generate FindModule or export find_package calls:

The most commonly used function are:

  • rapids_find_package(<project_name> BUILD_EXPORT_SET <name> INSTALL_EXPORT_SET <name> ) Combines find_package and support to track dependencies for easy package exporting
  • rapids_generate_module(<PackageName> HEADER_NAMES <paths...> LIBRARY_NAMES <names...> ) Generate a FindModule for the given package. Allows association to export sets so the generated FindModule can be shipped with the project

test

The rapids_test functions simplify CTest resource allocation, allowing for tests to run in parallel without overallocating GPU resources.

The most commonly used functions are:

  • rapids_test_add(NAME <test_name> GPUS <N> PERCENT <N>): State how many GPU resources a single test requires

Overriding RAPIDS.cmake

At times projects or developers will need to verify rapids-cmake branches. To do this you can set variables that control which repository RAPIDS.cmake downloads, which should be done like this:

  # To override the version that is pulled:
  set(rapids-cmake-version "<version>")

  # To override the GitHub repository:
  set(rapids-cmake-repo "<my_fork>")

  # To use an exact Git SHA:
  set(rapids-cmake-sha "<my_git_sha>")

  # To use a Git tag:
  set(rapids-cmake-tag "<my_git_tag>")

  # To override the repository branch:
  set(rapids-cmake-branch "<my_feature_branch>")

  # Or to override the entire repository URL (e.g. to use a GitLab repo):
  set(rapids-cmake-url "https://gitlab.com/<my_user>/<my_fork>/-/archive/<my_branch>/<my_fork>-<my_branch>.zip")

  file(DOWNLOAD https://raw.githubusercontent.com/rapidsai/rapids-cmake/branch-22.10/RAPIDS.cmake
      ${CMAKE_CURRENT_BINARY_DIR}/RAPIDS.cmake)
  include(${CMAKE_CURRENT_BINARY_DIR}/RAPIDS.cmake)

A few notes:

  • An explicitly defined rapids-cmake-url will always be used
  • rapids-cmake-sha takes precedence over rapids-cmake-tag
  • rapids-cmake-tag takes precedence over rapids-cmake-branch
  • It is advised to always set rapids-cmake-version to the version expected by the repo your modifications will pull

Contributing

Review the CONTRIBUTING.md file for information on how to contribute code and issues to the project.

Packages

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  • C++ 2.5%
  • Cuda 1.3%
  • Shell 1.2%
  • Python 1.2%