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Halide and CMake

This is a comprehensive guide to the three main usage stories of the Halide CMake build.

  1. Compiling or packaging Halide from source.
  2. Building Halide programs using the official CMake package.
  3. Contributing to Halide and updating the build files.

The following sections cover each in detail.

Table of Contents

Getting started

This section covers installing a recent version of CMake and the correct dependencies for building and using Halide. If you have not used CMake before, we strongly suggest reading through the CMake documentation first.

Installing CMake

Halide requires at least version 3.16, which was released in November 2019. Fortunately, getting a recent version of CMake couldn't be easier, and there are multiple good options on any system to do so. Generally, one should always have the most recent version of CMake installed system-wide. CMake is committed to backwards compatibility and even the most recent release can build projects over a decade old.

Cross-platform

The Python package manager pip3 has the newest version of CMake at all times. This might be the most convenient method since Python 3 is an optional dependency for Halide, anyway.

$ pip3 install --upgrade cmake

See the PyPI website for more details.

Windows

On Windows, there are three primary methods for installing an up-to-date CMake:

  1. If you have Visual Studio 2019 installed, you can get CMake 3.17 through the Visual Studio installer. This is the recommended way of getting CMake if you are able to use Visual Studio 2019. See Microsoft's documentation for more details.
  2. If you use Chocolatey, its CMake package is kept up to date. It should be as simple as choco install cmake.
  3. Otherwise, you should install CMake from Kitware's website.

macOS

On macOS, the Homebrew CMake package is kept up to date. Simply run:

$ brew update
$ brew install cmake

to install the newest version of CMake. If your environment prevents you from installing Homebrew, the binary release on Kitware's website is also a viable option.

Ubuntu Linux

There are a few good ways to install a modern CMake on Ubuntu:

  1. If you're on Ubuntu Linux 20.04 (focal), then simply running sudo apt install cmake will get you CMake 3.16.
  2. If you are on an older Ubuntu release or would like to use the newest CMake, try installing via the snap store: snap install cmake. Be sure you do not already have cmake installed via APT. The snap package automatically stays up to date.
  3. For older versions of Debian, Ubuntu, Mint, and derivatives, Kitware provides an APT repository with up-to-date releases. Note that this is still useful for Ubuntu 20.04 because it will remain up to date.
  4. If all else fails, you might need to build CMake from source (eg. on old Ubuntu versions running on ARM). In that case, follow the directions posted on Kitware's website.

For other Linux distributions, check with your distribution's package manager or use pip as detailed above. Snap packages might also be available.

Note: On WSL 1, the snap service is not available; in this case, prefer to use the APT repository. On WSL 2, all methods are available.

Installing dependencies

We generally recommend using a package manager to fetch Halide's dependencies. Except where noted, we recommend using vcpkg on Windows, Homebrew on macOS, and APT on Ubuntu 20.04 LTS.

Only LLVM and Clang are absolutely required to build Halide. Halide always supports three LLVM versions: the current major version, the previous major version, and trunk. The LLVM and Clang versions must match exactly. For most users, we recommend using a binary release of LLVM rather than building it yourself.

However, to run all of the tests and apps, an extended set is needed. This includes lld, Python 3, libpng, libjpeg, Doxygen, OpenBLAS, ATLAS, and Eigen3. While not required to build any part of Halide, we find that Ninja is the best backend build tool across all platforms.

Note that CMake has many special variables for overriding the locations of packages and executables. A partial list can be found in the "find module options" section below, and more can be found in the documentation for the CMake find_package command. Normally, you should prefer to make sure your environment is set up so that CMake can find dependencies automatically. For instance, if you want CMake to use a particular version of Python, create a virtual environment and activate it before configuring Halide.

Windows

We assume you have vcpkg installed at D:\vcpkg. Follow the instructions in the vcpkg README to install. Start by installing LLVM.

D:\vcpkg> .\vcpkg install llvm[target-all,enable-assertions,clang-tools-extra]:x64-windows
D:\vcpkg> .\vcpkg install llvm[target-all,enable-assertions,clang-tools-extra]:x86-windows

This will also install Clang and LLD. The enable-assertions option is not strictly necessary but will make debugging during development much smoother. These builds will take a long time and a lot of disk space. After they are built, it is safe to delete the intermediate build files and caches in D:\vcpkg\buildtrees and %APPDATA%\local\vcpkg.

Then install the other libraries:

D:\vcpkg> .\vcpkg install libpng:x64-windows libjpeg-turbo:x64-windows openblas:x64-windows eigen3:x64-windows
D:\vcpkg> .\vcpkg install libpng:x86-windows libjpeg-turbo:x86-windows openblas:x86-windows eigen3:x86-windows

To build the documentation, you will need to install Doxygen. This can be done either through Chocolatey or from the Doxygen website.

> choco install doxygen

To build the Python bindings, you will need to install Python 3. This should be done by running the official installer from the Python website. Be sure to download the debugging symbols through the installer. This will require using the "Advanced Installation" workflow. Although it is not strictly necessary, it is convenient to install Python system-wide on Windows (ie. C:\Program Files). This makes it easy for CMake to find without needing to manually set the PATH.

Once Python is installed, you can install the Python module dependencies either globally or in a virtual environment by running

> pip3 install -r .\python_bindings\requirements.txt

from the root of the repository.

If you would like to use Ninja, note that it is installed alongside CMake when using the Visual Studio 2019 installer. Alternatively, you can install via Chocolatey or place the pre-built binary from their website in the PATH.

> choco install ninja

macOS

On macOS, it is possible to install all dependencies via Homebrew:

$ brew install llvm libpng libjpeg [email protected] openblas doxygen ninja

The llvm package includes clang, clang-format, and lld, too. Don't forget to install the Python module dependencies:

$ pip3 install -r python_bindings/requirements.txt

Ubuntu

Finally, on Ubuntu 20.04 LTS, you should install the following packages (this includes the Python module dependencies):

dev@ubuntu:~$ sudo apt install \
                  clang-tools lld llvm-dev libclang-dev liblld-10-dev \
                  libpng-dev libjpeg-dev libgl-dev \
                  python3-dev python3-numpy python3-scipy python3-imageio python3-pybind11 \
                  libopenblas-dev libeigen3-dev libatlas-base-dev \
                  doxygen ninja-build

Building Halide with CMake

Basic build

These instructions assume that your working directory is the Halide repo root.

Windows

If you plan to use the Ninja generator, be sure to be in the developer command prompt corresponding to your intended environment. Note that whatever your intended target system (x86, x64, or arm), you must use the 64-bit host tools because the 32-bit tools run out of memory during the linking step with LLVM. More information is available from Microsoft's documentation.

You should either open the correct Developer Command Prompt directly or run the vcvarsall.bat script with the correct argument, ie. one of the following:

D:\> "C:\Program Files (x86)\Microsoft Visual Studio\2019\Community\VC\Auxiliary\Build\vcvarsall.bat" x64
D:\> "C:\Program Files (x86)\Microsoft Visual Studio\2019\Community\VC\Auxiliary\Build\vcvarsall.bat" x64_x86
D:\> "C:\Program Files (x86)\Microsoft Visual Studio\2019\Community\VC\Auxiliary\Build\vcvarsall.bat" x64_arm

Then, assuming that vcpkg is installed to D:\vcpkg, simply run:

> cmake -G Ninja -DCMAKE_BUILD_TYPE=Release -DCMAKE_TOOLCHAIN_FILE=D:\vcpkg\scripts\buildsystems\vcpkg.cmake -S . -B build
> cmake --build .\build

Valid values of CMAKE_BUILD_TYPE are Debug, RelWithDebInfo, MinSizeRel, and Release. When using a single-configuration generator (like Ninja) you must specify a build type when configuring Halide (or any other CMake project).

Otherwise, if you wish to create a Visual Studio based build system, you can configure with:

> cmake -G "Visual Studio 16 2019" -Thost=x64 -A x64 ^
        -DCMAKE_TOOLCHAIN_FILE=D:\vcpkg\scripts\buildsystems\vcpkg.cmake ^
        -S . -B build
> cmake --build .\build --config Release -j %NUMBER_OF_PROCESSORS%

Because the Visual Studio generator is a multi-config generator, you don't set CMAKE_BUILD_TYPE at configure-time, but instead pass the configuration to the build (and test/install) commands with the --config flag. More documentation is available in the CMake User Interaction Guide.

The process is similar for 32-bit:

> cmake -G "Visual Studio 16 2019" -Thost=x64 -A Win32 ^
        -DCMAKE_TOOLCHAIN_FILE=D:\vcpkg\scripts\buildsystems\vcpkg.cmake ^
        -S . -B build
> cmake --build .\build --config Release -j %NUMBER_OF_PROCESSORS%

In both cases, the -Thost=x64 flag ensures that the correct host tools are used.

Note: due to limitations in MSBuild, incremental builds using the VS generators will not detect changes to headers in the src/runtime folder. We recommend using Ninja for day-to-day development and use Visual Studio only if you need it for packaging.

macOS and Linux

The instructions here are straightforward. Assuming your environment is set up correctly, just run:

dev@host:~/Halide$ cmake -G Ninja -DCMAKE_BUILD_TYPE=Release -S . -B build
dev@host:~/Halide$ cmake --build ./build

If you omit -G Ninja, a Makefile-based generator will likely be used instead. In either case, CMAKE_BUILD_TYPE must be set to one of the standard types: Debug, RelWithDebInfo, MinSizeRel, or Release.

CMake Presets

If you are using CMake 3.19+, we provide several presets to make the above commands more convenient. The following CMake preset commands correspond to the longer ones above.

> cmake --preset=msvc-release  # Ninja generator, MSVC compiler, Release build
> cmake --preset=win64         # VS 2019 generator, 64-bit build
> cmake --preset=win32         # VS 2019 generator, 32-bit build
$ cmake --preset=gcc-release   # Ninja generator, GCC compiler, Release build

$ cmake --list-presets         # Get full list of presets.

The Windows and MSVC presets assume that the environment variable VCPKG_ROOT is set and points to the root of the vcpkg installation.

Note that the GCC presets do not define NDEBUG in release configurations, departing from the usual CMake behavior.

Installing

Once built, Halide will need to be installed somewhere before using it in a separate project. On any platform, this means running the cmake --install command in one of two ways. For a single-configuration generator (like Ninja), run either:

dev@host:~/Halide$ cmake --install ./build --prefix /path/to/Halide-install
> cmake --install .\build --prefix X:\path\to\Halide-install

For a multi-configuration generator (like Visual Studio) run:

dev@host:~/Halide$ cmake --install ./build --prefix /path/to/Halide-install --config Release
> cmake --install .\build --prefix X:\path\to\Halide-install --config Release

Of course, make sure that you build the corresponding config before attempting to install it.

Build options

Halide reads and understands several options that can configure the build. The following are the most consequential and control how Halide is actually compiled.

Option Default Description
BUILD_SHARED_LIBS ON Standard CMake variable that chooses whether to build as a static or shared library.
Halide_BUNDLE_LLVM OFF When building Halide as a static library, unpack the LLVM static libraries and add those objects to libHalide.a.
Halide_SHARED_LLVM OFF Link to the shared version of LLVM. Not available on Windows.
Halide_ENABLE_RTTI inherited from LLVM Enable RTTI when building Halide. Recommended to be set to ON
Halide_CLANG_TIDY_BUILD OFF Used internally to generate fake compile jobs for runtime files when running clang-tidy.
Halide_ENABLE_EXCEPTIONS ON Enable exceptions when building Halide
Halide_USE_CODEMODEL_LARGE OFF Use the Large LLVM codemodel
Halide_TARGET empty The default target triple to use for add_halide_library (and the generator tests, by extension)
Halide_CCACHE_BUILD OFF Use ccache to accelerate rebuilds.

The following options are only available when building Halide directly, ie. not through the add_subdirectory or FetchContent mechanisms. They control whether non-essential targets (like tests and documentation) are built.

Option Default Description
WITH_TESTS ON Enable building unit and integration tests
WITH_PYTHON_BINDINGS ON if Python found Enable building Python 3.x bindings
WITH_DOCS OFF Enable building the documentation via Doxygen
WITH_UTILS ON Enable building various utilities including the trace visualizer
WITH_TUTORIALS ON Enable building the tutorials

The following options control whether to build certain test subsets. They only apply when WITH_TESTS=ON:

Option Default Description
WITH_TEST_AUTO_SCHEDULE ON enable the auto-scheduling tests
WITH_TEST_CORRECTNESS ON enable the correctness tests
WITH_TEST_ERROR ON enable the expected-error tests
WITH_TEST_WARNING ON enable the expected-warning tests
WITH_TEST_PERFORMANCE ON enable performance testing
WITH_TEST_GENERATOR ON enable the AOT generator tests

The following options enable/disable various LLVM backends (they correspond to LLVM component names):

Option Default Description
TARGET_AARCH64 ON, if available Enable the AArch64 backend
TARGET_AMDGPU ON, if available Enable the AMD GPU backend
TARGET_ARM ON, if available Enable the ARM backend
TARGET_HEXAGON ON, if available Enable the Hexagon backend
TARGET_MIPS ON, if available Enable the MIPS backend
TARGET_NVPTX ON, if available Enable the NVidia PTX backend
TARGET_POWERPC ON, if available Enable the PowerPC backend
TARGET_RISCV ON, if available Enable the RISC V backend
TARGET_WEBASSEMBLY ON, if available Enable the WebAssembly backend. Only valid for LLVM 11+.
TARGET_X86 ON, if available Enable the x86 (and x86_64) backend

The following options enable/disable various Halide-specific backends:

Option Default Description
TARGET_OPENCL ON Enable the OpenCL-C backend
TARGET_METAL ON Enable the Metal backend
TARGET_D3D12COMPUTE ON Enable the Direct3D 12 Compute backend

The following options are WebAssembly-specific. They only apply when TARGET_WEBASSEMBLY=ON:

Option Default Description
WITH_WABT ON Include WABT Interpreter for WASM testing
WITH_WASM_SHELL ON Download a wasm shell (e.g. d8) for testing AOT wasm code.

Find module options

Halide uses the following find modules to search for certain dependencies. These modules accept certain variables containing hints for the search process. Before setting any of these variables, closely study the find_package documentation.

All of these variables should be set at the CMake command line via the -D flag.

First, Halide expects to find LLVM and Clang through the CONFIG mode of find_package. You can tell Halide where to find these dependencies by setting the corresponding _DIR variables:

Variable Description
LLVM_DIR $LLVM_ROOT/lib/cmake/LLVM/LLVMConfig.cmake
Clang_DIR $LLVM_ROOT/lib/cmake/Clang/ClangConfig.cmake

Here, $LLVM_ROOT is assumed to point to the root of an LLVM installation tree. This is either a system path or one produced by running cmake --install (as detailed in the main README.md). When building LLVM (and any other CONFIG packages) manually, it is a common mistake to point CMake to a build tree rather than an install tree. Doing so often produces inscrutable errors.

When using CMake 3.18 or above, some of Halide's tests will search for CUDA using the FindCUDAToolkit module. If it doesn't find your CUDA installation automatically, you can point it to it by setting:

Variable Description
CUDAToolkit_ROOT Path to the directory containing bin/nvcc[.exe]
CUDA_PATH Environment variable, same as above.

If the CMake version is lower than 3.18, the deprecated FindCUDA module will be used instead. It reads the variable CUDA_TOOLKIT_ROOT_DIR instead of CUDAToolkit_ROOT above.

TODO(halide#5633): update this section for OpenGLCompute, which needs some (but maybe not all) of this.

When targeting OpenGL, the FindOpenGL and FindX11 modules will be used to link AOT generated binaries. These modules can be overridden by setting the following variables:

Variable Description
OPENGL_egl_LIBRARY Path to the EGL library.
OPENGL_glu_LIBRARY Path to the GLU library.
OPENGL_glx_LIBRARY Path to the GLVND GLX library.
OPENGL_opengl_LIBRARY Path to the GLVND OpenGL library
OPENGL_gl_LIBRARY Path to the OpenGL library.

The OpenGL paths will need to be set if you intend to use OpenGL with X11 on macOS.

Halide also searches for libpng and libjpeg-turbo through the FindPNG and FindJPEG modules, respectively. They can be overridden by setting the following variables.

Variable Description
PNG_LIBRARIES Paths to the libraries to link against to use PNG.
PNG_INCLUDE_DIRS Path to png.h, etc.
JPEG_LIBRARIES Paths to the libraries needed to use JPEG.
JPEG_INCLUDE_DIRS Paths to jpeglib.h, etc.

When WITH_DOCS is set to ON, Halide searches for Doxygen using the FindDoxygen module. It can be overridden by setting the following variable.

Variable Description
DOXYGEN_EXECUTABLE Path to the Doxygen executable.

When compiling for an OpenCL target, Halide uses the FindOpenCL target to locate the libraries and include paths. These can be overridden by setting the following variables:

Variable Description
OpenCL_LIBRARIES Paths to the libraries to link against to use OpenCL.
OpenCL_INCLUDE_DIRS Include directories for OpenCL.

Lastly, Halide searches for Python 3 using the FindPython3 module, not the deprecated FindPythonInterp and FindPythonLibs modules, like other projects you might have encountered. You can select which Python installation to use by setting the following variable.

Variable Description
Python3_ROOT_DIR Define the root directory of a Python 3 installation.

Using Halide from your CMake build

This section assumes some basic familiarity with CMake but tries to be explicit in all its examples. To learn more about CMake, consult the documentation and engage with the community on the CMake Discourse.

Note: previous releases bundled a halide.cmake module that was meant to be include()-ed into your project. This has been removed. Please upgrade to the new package config module.

A basic CMake project

There are two main ways to use Halide in your application: as a JIT compiler for dynamic pipelines or an ahead-of-time (AOT) compiler for static pipelines. CMake provides robust support for both use cases.

No matter how you intend to use Halide, you will need some basic CMake boilerplate.

cmake_minimum_required(VERSION 3.16)
project(HalideExample)

set(CMAKE_CXX_STANDARD 17)  # or newer
set(CMAKE_CXX_STANDARD_REQUIRED YES)
set(CMAKE_CXX_EXTENSIONS NO)

find_package(Halide REQUIRED)

The cmake_minimum_required command is required to be the first command executed in a CMake program. It disables all of the deprecated behavior ("policies" in CMake lingo) from earlier versions. The project command sets the name of the project (and has arguments for versioning, language support, etc.) and is required by CMake to be called immediately after setting the minimum version.

The next three variables set the project-wide C++ standard. The first, CMAKE_CXX_STANDARD, simply sets the standard version. Halide requires at least C++17. The second, CMAKE_CXX_STANDARD_REQUIRED, tells CMake to fail if the compiler cannot provide the requested standard version. Lastly, CMAKE_CXX_EXTENSIONS tells CMake to disable vendor-specific extensions to C++. This is not necessary to simply use Halide, but we require it when authoring new code in the Halide repo.

Finally, we use find_package to locate Halide on your system. If Halide is not globally installed, you will need to add the root of the Halide installation directory to CMAKE_PREFIX_PATH at the CMake command line.

dev@ubuntu:~/myproj$ cmake -G Ninja -DCMAKE_BUILD_TYPE=Release -DCMAKE_PREFIX_PATH="/path/to/Halide-install" -S . -B build

JIT mode

To use Halide in JIT mode (like the tutorials do, for example), you can simply link to Halide::Halide.

# ... same project setup as before ...
add_executable(my_halide_app main.cpp)
target_link_libraries(my_halide_app PRIVATE Halide::Halide)

Then Halide.h will be available to your code and everything should just work. That's it!

AOT mode

Using Halide in AOT mode is more complicated so we'll walk through it step by step. Note that this only applies to Halide generators, so it might be useful to re-read the tutorial on generators. Assume (like in the tutorial) that you have a source file named my_generators.cpp and that in it you have generator classes MyFirstGenerator and MySecondGenerator with registered names my_first_generator and my_second_generator respectively.

Then the first step is to add a generator executable to your build:

# ... same project setup as before ...
add_executable(my_generators my_generators.cpp)
target_link_libraries(my_generators PRIVATE Halide::Generator)

Using the generator executable, we can add a Halide library corresponding to MyFirstGenerator.

# ... continuing from above
add_halide_library(my_first_generator FROM my_generators)

This will create a static library target in CMake that corresponds to the output of running your generator. The second generator in the file requires generator parameters to be passed to it. These are also easy to handle:

# ... continuing from above
add_halide_library(my_second_generator FROM my_generators
                   PARAMS parallel=false scale=3.0 rotation=ccw output.type=uint16)

Adding multiple configurations is easy, too:

# ... continuing from above
add_halide_library(my_second_generator_2 FROM my_generators
                   GENERATOR my_second_generator
                   PARAMS scale=9.0 rotation=ccw output.type=float32)

add_halide_library(my_second_generator_3 FROM my_generators
                   GENERATOR my_second_generator
                   PARAMS parallel=false output.type=float64)

Here, we had to specify which generator to use (my_second_generator) since it uses the target name by default. The functions in these libraries will be named after the target names, my_second_generator_2 and my_second_generator_3, by default, but it is possible to control this via the FUNCTION_NAME parameter.

Each one of these targets, <GEN>, carries an associated <GEN>.runtime target, which is also a static library containing the Halide runtime. It is transitively linked through <GEN> to targets that link to <GEN>. On an operating system like Linux, where weak linking is available, this is not an issue. However, on Windows, this can fail due to symbol redefinitions. In these cases, you must declare that two Halide libraries share a runtime, like so:

# ... updating above
add_halide_library(my_second_generator_2 FROM my_generators
                   GENERATOR my_second_generator
                   USE_RUNTIME my_first_generator.runtime
                   PARAMS scale=9.0 rotation=ccw output.type=float32)

add_halide_library(my_second_generator_3 FROM my_generators
                   GENERATOR my_second_generator
                   USE_RUNTIME my_first_generator.runtime
                   PARAMS parallel=false output.type=float64)

This will even work correctly when different combinations of targets are specified for each halide library. A "greatest common denominator" target will be chosen that is compatible with all of them (or the build will fail).

Autoschedulers

When the autoschedulers are included in the release package, they are very simple to apply to your own generators. For example, we could update the definition of the my_first_generator library above to use the Adams2019 autoscheduler:

add_halide_library(my_second_generator FROM my_generators
                   AUTOSCHEDULER Halide::Adams2019
                   PARAMS auto_schedule=true)

RunGenMain

Halide provides a generic driver for generators to be used during development for benchmarking and debugging. Suppose you have a generator executable called my_gen and a generator within called my_filter. Then you can pass a variable name to the REGISTRATION parameter of add_halide_library which will contain the name of a generated C++ source that should be linked to Halide::RunGenMain and my_filter.

For example:

add_halide_library(my_filter FROM my_gen
                   REGISTRATION filter_reg_cpp)
add_executable(runner ${filter_reg_cpp})
target_link_libraries(runner PRIVATE my_filter Halide::RunGenMain)

Then you can run, debug, and benchmark your generator through the runner executable.

Halide package documentation

Halide provides a CMake package configuration module. The intended way to use the CMake build is to run find_package(Halide ...) in your CMakeLists.txt file. Closely read the find_package documentation before proceeding.

Components

The Halide package script understands a handful of optional components when loading the package.

First, if you plan to use the Halide Image IO library, you will want to include the png and jpeg components when loading Halide.

Second, Halide releases can contain a variety of configurations: static, shared, debug, release, etc. CMake handles Debug/Release configurations automatically, but generally only allows one type of library to be loaded.

The package understands two components, static and shared, that specify which type of library you would like to load. For example, if you want to make sure that you link against shared Halide, you can write:

find_package(Halide REQUIRED COMPONENTS shared)

If the shared libraries are not available, this will result in a failure.

If no component is specified, then the Halide_SHARED_LIBS variable is checked. If it is defined and set to true, then the shared libraries will be loaded or the package loading will fail. Similarly, if it is defined and set to false, the static libraries will be loaded.

If no component is specified and Halide_SHARED_LIBS is not defined, then the BUILD_SHARED_LIBS variable will be inspected. If it is not defined or defined and set to true, then it will attempt to load the shared libs and fall back to the static libs if they are not available. Similarly, if BUILD_SHARED_LIBS is defined and set to false, then it will try the static libs first then fall back to the shared libs.

Variables

Variables that control package loading:

Variable Description
Halide_SHARED_LIBS override BUILD_SHARED_LIBS when loading the Halide package via find_package. Has no effect when using Halide via add_subdirectory as a Git or FetchContent submodule.

Variables set by the package:

Variable Description
Halide_VERSION The full version string of the loaded Halide package
Halide_VERSION_MAJOR The major version of the loaded Halide package
Halide_VERSION_MINOR The minor version of the loaded Halide package
Halide_VERSION_PATCH The patch version of the loaded Halide package
Halide_VERSION_TWEAK The tweak version of the loaded Halide package
Halide_HOST_TARGET The Halide target triple corresponding to "host" for this build.
Halide_ENABLE_EXCEPTIONS Whether Halide was compiled with exception support
Halide_ENABLE_RTTI Whether Halide was compiled with RTTI

Imported targets

Halide defines the following targets that are available to users:

Imported target Description
Halide::Halide this is the JIT-mode library to use when using Halide from C++.
Halide::Generator this is the target to use when defining a generator executable. It supplies a main() function.
Halide::Runtime adds include paths to the Halide runtime headers
Halide::Tools adds include paths to the Halide tools, including the benchmarking utility.
Halide::ImageIO adds include paths to the Halide image IO utility and sets up dependencies to PNG / JPEG if they are available.
Halide::RunGenMain used with the REGISTRATION parameter of add_halide_library to create simple runners and benchmarking tools for Halide libraries.

The following targets are not guaranteed to be available:

Imported target Description
Halide::Python this is a Python 3 module that can be referenced as $<TARGET_FILE:Halide::Python> when setting up Python tests or the like from CMake.
Halide::Adams19 the Adams et.al. 2019 autoscheduler (no GPU support)
Halide::Li18 the Li et.al. 2018 gradient autoscheduler (limited GPU support)

Functions

Currently, only one function is defined:

add_halide_library

This is the main function for managing generators in AOT compilation. The full signature follows:

add_halide_library(<target> FROM <generator-target>
                   [GENERATOR generator-name]
                   [FUNCTION_NAME function-name]
                   [NAMESPACE cpp-namespace]
                   [USE_RUNTIME hl-target]
                   [PARAMS param1 [param2 ...]]
                   [TARGETS target1 [target2 ...]]
                   [FEATURES feature1 [feature2 ...]]
                   [PLUGINS plugin1 [plugin2 ...]]
                   [AUTOSCHEDULER scheduler-name]
                   [GRADIENT_DESCENT]
                   [C_BACKEND]
                   [REGISTRATION OUTVAR]
                   [HEADER OUTVAR]
                   [<extra-output> OUTVAR])

extra-output = ASSEMBLY | BITCODE | COMPILER_LOG | CPP_STUB
             | FEATURIZATION | LLVM_ASSEMBLY | PYTHON_EXTENSION
             | PYTORCH_WRAPPER | SCHEDULE | STMT | STMT_HTML

This function creates a called <target> corresponding to running the <generator-target> (an executable target which links to Halide::Generator) one time, using command line arguments derived from the other parameters.

The arguments GENERATOR and FUNCTION_NAME default to <target>. They correspond to the -g and -f command line flags, respectively.

NAMESPACE is syntactic sugar to specify the C++ namespace (if any) of the generated function; you can also specify the C++ namespace (if any) directly in the FUNCTION_NAME argument, but for repeated declarations or very long namespaces, specifying this separately can provide more readable build files.

If USE_RUNTIME is not specified, this function will create another target called <target>.runtime which corresponds to running the generator with -r and a compatible list of targets. This runtime target is an INTERFACE dependency of <target>. If multiple runtime targets need to be linked together, setting USE_RUNTIME to another Halide library, <target2> will prevent the generation of <target>.runtime and instead use <target2>.runtime.

Parameters can be passed to a generator via the PARAMS argument. Parameters should be space-separated. Similarly, TARGETS is a space-separated list of targets for which to generate code in a single function. They must all share the same platform/bits/os triple (eg. arm-32-linux). Features that are in common among all targets, including device libraries (like cuda) should go in FEATURES.

Every element of TARGETS must begin with the same arch-bits-os triple. This function understands two meta-triples, host and cmake. The meta-triple host is equal to the arch-bits-os triple used to compile Halide along with all of the supported instruction set extensions. On platforms that support running both 32 and 64-bit programs, this will not necessarily equal the platform the compiler is running on or that CMake is targeting.

The meta-triple cmake is equal to the arch-bits-os of the current CMake target. This is useful if you want to make sure you are not unintentionally cross-compiling, which would result in an IMPORTED target being created. When TARGETS is empty and the host target would not cross-compile, then host will be used. Otherwise, cmake will be used and an author warning will be issued.

To set the default autoscheduler, set the AUTOSCHEDULER argument to a target named like Namespace::Scheduler, for example Halide::Adams19. This will set the -s flag on the generator command line to Scheduler and add the target to the list of plugins. Additional plugins can be loaded by setting the PLUGINS argument. If the argument to AUTOSCHEDULER does not contain :: or it does not name a target, it will be passed to the -s flag verbatim.

If GRADIENT_DESCENT is set, then the module will be built suitably for gradient descent calculation in TensorFlow or PyTorch. See Generator::build_gradient_module() for more documentation. This corresponds to passing -d 1 at the generator command line.

If the C_BACKEND option is set, this command will invoke the configured C++ compiler on a generated source. Note that a <target>.runtime target is not created in this case, and the USE_RUNTIME option is ignored. Other options work as expected.

If REGISTRATION is set, the path (relative to CMAKE_CURRENT_BINARY_DIR) to the generated .registration.cpp file will be set in OUTVAR. This can be used to generate a runner for a Halide library that is useful for benchmarking and testing, as documented above. This is equivalent to setting -e registration at the generator command line.

If HEADER is set, the path (relative to CMAKE_CURRENT_BINARY_DIR) to the generated .h header file will be set in OUTVAR. This can be used with install(FILES) to conveniently deploy the generated header along with your library.

Lastly, each of the extra-output arguments directly correspond to an extra output (via -e) from the generator. The value OUTVAR names a variable into which a path (relative to CMAKE_CURRENT_BINARY_DIR) to the extra file will be written.

Cross compiling

Cross-compiling in CMake can be tricky, since CMake doesn't easily support compiling for both the host platform and the cross-platform within the same build. Unfortunately, Halide generator executables are just about always designed to run on the host platform. Each project will be set up differently and have different requirements, but here are some suggestions for effective use of CMake in these scenarios.

Use a super-build

A CMake super-build consists of breaking down a project into sub-projects that are isolated by toolchain. The basic structure is to have an outermost project that only coordinates the sub-builds via the ExternalProject module.

One would then use Halide to build a generator executable in one self-contained project, then export that target to be used in a separate project. The second project would be configured with the target toolchain and would call add_halide_library with no TARGETS option and set FROM equal to the name of the imported generator executable. Obviously, this is a significant increase in complexity over a typical CMake project.

Use ExternalProject directly

A lighter weight alternative to the above is to use ExternalProject directly in your parent build. Configure the parent build with the target toolchain, and configure the inner project to use the host toolchain. Then, manually create an IMPORTED target for your generator executable and call add_halide_library as described above.

The main drawback of this approach is that creating accurate IMPORTED targets is difficult since predicting the names and locations of your binaries across all possible platform and CMake project generators is difficult. In particular, it is hard to predict executable extensions in cross-OS builds.

Use an emulator or run on device

The CMAKE_CROSSCOMPILING_EMULATOR variable allows one to specify a command prefix to run a target-system binary on the host machine. One could set this to a custom shell script that uploads the generator executable, runs it on the device and copies back the results.

Bypass CMake

The previous two options ensure that the targets generated by add_halide_library will be normal static libraries. This approach does not use ExternalProject, but instead produces IMPORTED targets. The main drawback of IMPORTED targets is that they are considered second-class in CMake. In particular, they cannot be installed with the typical install(TARGETS) command. Instead, they must be installed using install(FILES) and the $<TARGET_FILE:tgt> generator expression.

Contributing CMake code to Halide

When contributing new CMake code to Halide, keep in mind that the minimum version is 3.16. Therefore, it is possible (and indeed required) to use modern CMake best practices.

Like any large and complex system with a dedication to preserving backwards compatibility, CMake is difficult to learn and full of traps. While not comprehensive, the following serves as a guide for writing quality CMake code and outlines the code quality expectations we have as they apply to CMake.

General guidelines and best practices

The following are some common mistakes that lead to subtly broken builds.

  • Reading the build directory. While setting up the build, the build directory should be considered write only. Using the build directory as a read/write temporary directory is acceptable as long as all temp files are cleaned up by the end of configuration.
  • Not using generator expressions. Declarative is better than imperative and this is no exception. Conditionally adding to a target property can leak unwanted details about the build environment into packages. Some information is not accurate or available except via generator expressions, eg. the build configuration.
  • Using the wrong variable. CMAKE_SOURCE_DIR doesn't always point to the Halide source root. When someone uses Halide via FetchContent, it will point to their source root instead. The correct variable is Halide_SOURCE_DIR. If you want to know if the compiler is MSVC, check it directly with the MSVC variable; don't use WIN32. That will be wrong when compiling with clang on Windows. In most cases, however, a generator expression will be more appropriate.
  • Using directory properties. Directory properties have vexing behavior and are essentially deprecated from CMake 3.0+. Propagating target properties is the way of the future.
  • Using the wrong visibility. Target properties can be PRIVATE, INTERFACE, or both (aka PUBLIC). Pick the most conservative one for each scenario. Refer to the transitive usage requirements docs for more information.
  • Needlessly expanding variables The if and foreach commands generally expand variables when provided by name. Expanding such variables manually can unintentionally change the behavior of the command. Use foreach (item IN LISTS list) instead of foreach (item ${list}). Similarly, use if (varA STREQUAL varB) instead of if ("${varA}" STREQUAL "${varB}") and definitely don't use if (${varA} STREQUAL ${varB}) since that will fail (in the best case) if either variable's value contains a semi-colon (due to argument expansion).

Prohibited commands list

As mentioned above, using directory properties is brittle and they are therefore not allowed. The following functions may not appear in any new CMake code.

Command Alternative
add_compile_definitions Use target_compile_definitions
add_compile_options Use target_compile_options
add_definitions Use target_compile_definitions
add_link_options Use target_link_options, but prefer not to use either
get_directory_property Use cache variables or target properties
get_property(... DIRECTORY) Use cache variables or target properties
include_directories Use target_include_directories
link_directories Use target_link_libraries
link_libraries Use target_link_libraries
remove_definitions Generator expressions in target_compile_definitions
set_directory_properties Use cache variables or target properties
set_property(... DIRECTORY) Use cache variables or target properties
target_link_libraries(target lib) Use target_link_libraries with a visibility specifier (eg. PRIVATE)

As an example, it was once common practice to write code similar to this:

# WRONG: do not do this
include_directories(include)
add_library(my_lib source1.cpp ..)

However, this has two major pitfalls. First, it applies to all targets created in that directory, even those before the call to include_directories and those created in include()-ed CMake files. As CMake files get larger and more complex, this behavior gets harder to pinpoint. This is particularly vexing when using the link_libraries or add_defintions commands. Second, this form does not provide a way to propagate the include directory to consumers of my_lib. The correct way to do this is:

# CORRECT
add_library(my_lib source1.cpp ...)
target_include_directories(my_lib PUBLIC $<BUILD_INTERFACE:include>)

This is better in many ways. It only affects the target in question. It propagates the include path to the targets linking to it (via PUBLIC). It also does not incorrectly export the host-filesystem-specific include path when installing or packaging the target (via $<BUILD_INTERFACE>).

If common properties need to be grouped together, use an INTERFACE target (better) or write a function (worse). There are also several functions that are disallowed for other reasons:

Command Reason Alternative
aux_source_directory Interacts poorly with incremental builds and Git List source files explicitly
build_command CTest internal function Use CTest build-and-test mode via CMAKE_CTEST_COMMAND
cmake_host_system_information Usually misleading information. Inspect toolchain variables and use generator expressions.
cmake_policy(... OLD) OLD policies are deprecated by definition. Instead, fix the code to work with the new policy.
create_test_sourcelist We use our own unit testing solution See the adding tests section.
define_property Adds unnecessary complexity Use a cache variable. Exceptions under special circumstances.
enable_language Halide is C/C++ only FindCUDAToolkit or FindCUDA, appropriately guarded.
file(GLOB ...) Interacts poorly with incremental builds and Git List source files explicitly. Allowed if not globbing for source files.
fltk_wrap_ui Halide does not use FLTK None
include_external_msproject Halide must remain portable Write a CMake package config file or find module.
include_guard Use of recursive inclusion is not allowed Write (recursive) functions.
include_regular_expression Changes default dependency checking behavior None
load_cache Superseded by FetchContent/ExternalProject Use aforementioned modules
macro CMake macros are not hygienic and are therefore error-prone Use functions instead.
site_name Privacy: do not want leak host name information Provide a cache variable, generate a unique name.
variable_watch Debugging helper None. Not needed in production.

Lastly, do not introduce any dependencies via find_package without broader approval. Confine dependencies to the dependencies/ subtree.

Prohibited variables list

Any variables that are specific to languages that are not enabled should, of course, be avoided. But of greater concern are variables that are easy to misuse or should not be overridden for our end-users. The following (non-exhaustive) list of variables shall not be used in code merged into master.

Variable Reason Alternative
CMAKE_ROOT Code smell Rely on find_package search options; include HINTS if necessary
CMAKE_DEBUG_TARGET_PROPERTIES Debugging helper None
CMAKE_FIND_DEBUG_MODE Debugging helper None
CMAKE_RULE_MESSAGES Debugging helper None
CMAKE_VERBOSE_MAKEFILE Debugging helper None
CMAKE_BACKWARDS_COMPATIBILITY Deprecated None
CMAKE_BUILD_TOOL Deprecated ${CMAKE_COMMAND} --build or CMAKE_MAKE_PROGRAM (but see below)
CMAKE_CACHEFILE_DIR Deprecated CMAKE_BINARY_DIR, but see below
CMAKE_CFG_INTDIR Deprecated $<CONFIG>, $<TARGET_FILE:..>, target resolution of add_custom_command, etc.
CMAKE_CL_64 Deprecated CMAKE_SIZEOF_VOID_P
CMAKE_COMPILER_IS_* Deprecated CMAKE_<LANG>_COMPILER_ID
CMAKE_HOME_DIRECTORY Deprecated CMAKE_SOURCE_DIR, but see below
CMAKE_DIRECTORY_LABELS Directory property None
CMAKE_BUILD_TYPE Only applies to single-config generators. $<CONFIG>
CMAKE_*_FLAGS* (w/o _INIT) User-only Write a toolchain file with the corresponding _INIT variable
CMAKE_COLOR_MAKEFILE User-only None
CMAKE_ERROR_DEPRECATED User-only None
CMAKE_CONFIGURATION_TYPES We only support the four standard build types None

Of course feel free to insert debugging helpers while developing but please remove them before review. Finally, the following variables are allowed, but their use must be motivated:

Variable Reason Alternative
CMAKE_SOURCE_DIR Points to global source root, not Halide's. Halide_SOURCE_DIR or PROJECT_SOURCE_DIR
CMAKE_BINARY_DIR Points to global build root, not Halide's Halide_BINARY_DIR or PROJECT_BINARY_DIR
CMAKE_MAKE_PROGRAM CMake abstracts over differences in the build tool. Prefer CTest's build and test mode or CMake's --build mode
CMAKE_CROSSCOMPILING Often misleading. Inspect relevant variables directly, eg. CMAKE_SYSTEM_NAME
BUILD_SHARED_LIBS Could override user setting None, but be careful to restore value when overriding for a dependency

Any use of these functions and variables will block a PR.

Adding tests

When adding a file to any of the folders under test, be aware that CI expects that every .c and .cpp appears in the CMakeLists.txt file on its own line, possibly as a comment. This is to avoid globbing and also to ensure that added files are not missed.

For most test types, it should be as simple as adding to the existing lists, which must remain in alphabetical order. Generator tests are trickier, but following the existing examples is a safe way to go.

Adding apps

If you're contributing a new app to Halide: great! Thank you! There are a few guidelines you should follow when writing a new app.

  • Write the app as if it were a top-level project. You should call find_package(Halide) and set the C++ version to 11.
  • Call enable_testing() and add a small test that runs the app.
  • Don't assume your app will have access to a GPU. Write your schedules to be robust to varying buildbot hardware.
  • Don't assume your app will be run on a specific OS, architecture, or bitness. Write your apps to be robust (ideally efficient) on all supported platforms.
  • If you rely on any additional packages, don't include them as REQUIRED, instead test to see if their targets are available and, if not, call return() before creating any targets. In this case, print a message(STATUS "[SKIP] ..."), too.
  • Look at the existing apps for examples.
  • Test your app with ctest before opening a PR. Apps are built as part of the test, rather than the main build.