Skip to content

halide/Halide

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Halide

Halide is a programming language designed to make it easier to write high-performance image and array processing code on modern machines. Halide currently targets:

  • CPU architectures: X86, ARM, Hexagon, PowerPC, RISC-V
  • Operating systems: Linux, Windows, macOS, Android, iOS, Qualcomm QuRT
  • GPU Compute APIs: CUDA, OpenCL, Apple Metal, Microsoft Direct X 12, Vulkan

Rather than being a standalone programming language, Halide is embedded in C++. This means you write C++ code that builds an in-memory representation of a Halide pipeline using Halide's C++ API. You can then compile this representation to an object file, or JIT-compile it and run it in the same process. Halide also provides a Python binding that provides full support for writing Halide embedded in Python without C++.

Halide requires C++17 (or later) to use.

For more detail about what Halide is, see https://halide-lang.org.

For API documentation see https://halide-lang.org/docs.

For some example code, read through the tutorials online at https://halide-lang.org/tutorials. The corresponding code is in the tutorials/ directory. Larger examples are in the apps/ directory.

If you've acquired a full source distribution and want to build Halide, see the notes below.

Getting Halide

Pip

As of Halide 19.0.0, we provide binary wheels on PyPI. Halide provides bindings for C++ and Python. Even if you only intend to use Halide from C++, pip may be the easiest way to get a binary build of Halide.

Full releases may be installed with pip like so:

$ pip install halide

Every commit to main is published to Test PyPI as a development version and these may be installed with a few extra flags:

$ pip install halide --pre --extra-index-url https://test.pypi.org/simple

Currently, we provide wheels for: Windows x86-64, macOS x86-64, macOS arm64, and Linux x86-64. The Linux wheels are built for manylinux_2_28, which makes them broadly compatible (Debian 10, Ubuntu 18.10, Fedora 29).

For C++ usage of the pip package: On Linux and macOS, CMake's find_package command should find Halide as long as you're in the same virtual environment you installed it in. On Windows, you will need to add the virtual environment root directory to CMAKE_PREFIX_PATH. This can be done by running set CMAKE_PREFIX_PATH=%VIRTUAL_ENV% in cmd.

Other build systems can find the Halide root path by running python -c "import halide; print(halide.install_dir())".

Homebrew

Alternatively, if you use macOS, you can install Halide via Homebrew like so:

$ brew install halide

Binary tarballs

The latest version of Halide can always be found on GitHub at https://github.com/halide/Halide/releases

We provide binary releases for many popular platforms and architectures, including 32/64-bit x86 Windows, 64-bit x86/ARM macOS, and 32/64-bit x86/ARM Ubuntu Linux.

The macOS releases are built using XCode's command-line tools with Apple Clang 500.2.76. This means that we link against libc++ instead of libstdc++. You may need to adjust compiler options accordingly if you're using an older XCode which does not default to libc++.

We use a recent Ubuntu LTS to build the Linux releases; if your distribution is too old, it might not have the requisite glibc.

Nightly builds of Halide and the LLVM versions we use in CI are also available at https://buildbot.halide-lang.org/

Vcpkg

If you use vcpkg to manage dependencies, you can install Halide via:

$ vcpkg install halide:x64-windows # or x64-linux/x64-osx

One caveat: vcpkg installs only the minimum Halide backends required to compile code for the active platform. If you want to include all the backends, you should install halide[target-all]:x64-windows instead. Note that since this will build LLVM, it will take a lot of disk space (up to 100GB).

Other package managers

We are interested in bringing Halide to other popular package managers and Linux distribution repositories! We track the status of various distributions of Halide in this GitHub issue. If you have experience publishing packages we would be happy to work with you!

Building Halide

Platform Support

There are two sets of platform requirements relevant to Halide: those required to run the compiler library in either JIT or AOT mode, and those required to run the binary outputs of the AOT compiler.

These are the tested host toolchain and platform combinations for building and running the Halide compiler library.

Compiler Version OS Architectures
GCC 9.5 Ubuntu Linux 20.04 LTS x86, x64
GCC 11.4 Ubuntu Linux 22.04 LTS ARM32, ARM64
MSVC 2022 (19.37) Windows 11 (22631) x86, x64
AppleClang 15.0.0 macOS 14.4.1 x64
AppleClang 14.0.0 macOS 14.6 ARM64

Some users have successfully built Halide for Linux using Clang 9.0.0+, for Windows using ClangCL 11.0.0+, and for Windows ARM64 by cross-compiling with MSVC. We do not actively test these scenarios, however, so your mileage may vary.

Beyond these, we are willing to support (by accepting PRs for) platform and toolchain combinations that still receive active, first-party, public support from their original vendors. For instance, at time of writing, this excludes Windows 7 and includes Ubuntu 18.04 LTS.

Compiled AOT pipelines are expected to have much broader platform support. The binaries use the C ABI, and we expect any compliant C compiler to be able to use the generated headers correctly. The C++ bindings currently require C++17. If you discover a compatibility problem with a generated pipeline, please open an issue.

Acquiring LLVM

At any point in time, building Halide requires either the latest stable version of LLVM, the previous stable version of LLVM, or trunk. At the time of writing, this means versions 19, 18, and 17 are supported, but 16 is not.

It is simplest to get a binary release of LLVM on macOS by using Homebrew. Just run brew install llvm. On Debian flavors of Linux, the LLVM APT repo is best; use the provided installation script. We know of no suitable official binary releases for Windows, however the ones we use in CI can usually be found at https://buildbot.halide-lang.org, along with tarballs for our other tested platforms. See the section on Windows below for further advice.

If your OS does not have packages for LLVM, or you want more control over the configuration, you can build it yourself. First check it out from GitHub:

$ git clone --depth 1 --branch llvmorg-18.1.8 https://github.com/llvm/llvm-project.git

(LLVM 18.1.8 is the most recent released LLVM at the time of writing. For current trunk, use main instead)

Then build it like so:

$ cmake -G Ninja -S llvm-project/llvm -B build \
        -DCMAKE_BUILD_TYPE=Release \
        -DLLVM_ENABLE_PROJECTS="clang;lld;clang-tools-extra" \
        -DLLVM_ENABLE_RUNTIMES=compiler-rt \
        -DLLVM_TARGETS_TO_BUILD="WebAssembly;X86;AArch64;ARM;Hexagon;NVPTX;PowerPC;RISCV" \
        -DLLVM_ENABLE_ASSERTIONS=ON \
        -DLLVM_ENABLE_EH=ON \
        -DLLVM_ENABLE_RTTI=ON \
        -DLLVM_ENABLE_HTTPLIB=OFF \
        -DLLVM_ENABLE_LIBEDIT=OFF \
        -DLLVM_ENABLE_LIBXML2=OFF \
        -DLLVM_ENABLE_TERMINFO=OFF \
        -DLLVM_ENABLE_ZLIB=OFF \
        -DLLVM_ENABLE_ZSTD=OFF \
        -DLLVM_BUILD_32_BITS=OFF
$ cmake --build build
$ cmake --install build --prefix llvm-install

This will produce a working LLVM installation in $PWD/llvm-install. We refer to this path as LLVM_ROOT later. Do not confuse this installation tree with the build tree!

LLVM takes a long time to build, so the above command uses Ninja to maximize parallelism. If you choose to omit -G Ninja, Makefiles will be generated instead. In this case, enable parallelism with cmake --build build -j NNN where NNN is the number of parallel jobs, i.e. the number of CPUs you have.

Note that you must add clang and lld to LLVM_ENABLE_PROJECTS and WebAssembly and X86 must be included in LLVM_TARGETS_TO_BUILD. LLVM_ENABLE_RUNTIMES=compiler-rt is only required to build the fuzz tests, and clang-tools-extra is only necessary if you plan to contribute code to Halide (so that you can run clang-tidy on your pull requests). You can disable exception handling (EH) and RTTI if you don't want the Python bindings. We recommend enabling the full set to simplify builds during development.

Building Halide with CMake

This is discussed in greater detail in BuildingHalideWithCMake.md. CMake version 3.28+ is required to build Halide.

MacOS and Linux

Follow the above instructions to build LLVM or acquire a suitable binary release. Then change directory to the Halide repository and run:

$ cmake -G Ninja  -S . -B build -DCMAKE_BUILD_TYPE=Release -DHalide_LLVM_ROOT=$LLVM_ROOT
$ cmake --build build

Setting -DHalide_LLVM_ROOT is not required if you have a suitable system-wide version installed. However, if you have multiple LLVMs installed, it can pick between them.

Windows

We suggest building with Visual Studio 2022. Your mileage may vary with earlier versions. Be sure to install the "C++ CMake tools for Windows" in the Visual Studio installer. For older versions of Visual Studio, do not install the CMake tools, but instead acquire CMake and Ninja from their respective project websites.

These instructions start from the D: drive. We assume this git repo is cloned to D:\Halide. We also assume that your shell environment is set up correctly. For a 64-bit build, run:

D:\> "C:\Program Files (x86)\Microsoft Visual Studio\2022\Community\VC\Auxiliary\Build\vcvarsall.bat" x64

For a 32-bit build, run:

D:\> "C:\Program Files (x86)\Microsoft Visual Studio\2022\Community\VC\Auxiliary\Build\vcvarsall.bat" x64_x86

Managing dependencies with vcpkg

The best way to get compatible dependencies on Windows is to use vcpkg. Install it like so:

D:\> git clone https://github.com/Microsoft/vcpkg.git
D:\> cd vcpkg
D:\vcpkg> .\bootstrap-vcpkg.bat -disableMetrics
...
CMake projects should use: "-DCMAKE_TOOLCHAIN_FILE=D:/vcpkg/scripts/buildsystems/vcpkg.cmake"

When using the toolchain file, vcpkg will automatically build all the necessary dependencies. However, as stated above, be aware that acquiring LLVM this way may use over 100 GB of disk space for its build trees and take a very long time to build. You can manually delete the build trees afterward, but vcpkg will not do this automatically.

See BuildingHalideWithCMake.md for directions to use Vcpkg for everything except LLVM.

Building Halide

Create a separate build tree and call CMake with vcpkg's toolchain. This will build in either 32-bit or 64-bit depending on the environment script (vcvars) that was run earlier.

D:\Halide> cmake -G Ninja -S . -B build ^
                 --toolchain D:/vcpkg/scripts/buildsystems/vcpkg.cmake ^
                 -DCMAKE_BUILD_TYPE=Release

Then run the build with:

D:\Halide> cmake --build build

To run all the tests:

D:\Halide> ctest --test-dir build --output-on-failure

Subsets of the tests can be selected with -L and include correctness, generator, error, and the other directory names under tests/.

Building LLVM (optional)

Follow these steps if you want to build LLVM yourself. First, download LLVM's sources (these instructions use the 18.1.8 release).

D:\> git clone --depth 1 --branch llvm-org-18.1.8 https://github.com/llvm/llvm-project.git

As above, run vcvarsall.bat to pick between x86 and x64. Then configure LLVM with the following command (for 32-bit, set -DLLVM_BUILD_32_BITS=ON instead):

D:\> cmake -G Ninja -S llvm-project\llvm -B build ^
           -DCMAKE_BUILD_TYPE=Release ^
           -DLLVM_ENABLE_PROJECTS=clang;lld;clang-tools-extra ^
           -DLLVM_ENABLE_RUNTIMES=compiler-rt ^
           -DLLVM_TARGETS_TO_BUILD=WebAssembly;X86;AArch64;ARM;Hexagon;NVPTX;PowerPC;RISCV ^
           -DLLVM_ENABLE_ASSERTIONS=ON ^
           -DLLVM_ENABLE_EH=ON ^
           -DLLVM_ENABLE_RTTI=ON ^
           -DLLVM_ENABLE_HTTPLIB=OFF ^
           -DLLVM_ENABLE_LIBEDIT=OFF ^
           -DLLVM_ENABLE_LIBXML2=OFF ^
           -DLLVM_ENABLE_TERMINFO=OFF ^
           -DLLVM_ENABLE_ZLIB=OFF ^
           -DLLVM_ENABLE_ZSTD=OFF ^
           -DLLVM_BUILD_32_BITS=OFF

MSBuild: If you want to build LLVM with MSBuild instead of Ninja, use -G "Visual Studio 17 2022" -Thost=x64 -A x64 or -G "Visual Studio 17 2022" -Thost=x64 -A Win32 in place of -G Ninja.

Finally, run the build and install to a local directory:

D:\> cmake --build build --config Release
D:\> cmake --install build --prefix llvm-install

You can substitute Debug for Release in the above cmake commands if you want a debug build.

To use this with Halide, but still allow vcpkg to manage other dependencies, you must add two flags to Halide's CMake configure command line. First, disable LLVM with -DVCPKG_OVERLAY_PORTS=cmake/vcpkg. Second, point CMake to our newly built Halide with -DHalide_LLVM_ROOT=D:/llvm-install.

If all else fails...

Do what the buildbots do: https://buildbot.halide-lang.org/master/#/builders

If the row that best matches your system is red, then maybe things aren't just broken for you. If it's green, then you can click through to the latest build and see the commands that the build bots run. Open a step ("Configure Halide" is useful) and look at the "stdio" logs in the viewer. These logs contain the full commands that were run, as well as the environment variables they were run with.

Building Halide with make

Warning

We do not provide support for the Makefile. Feel free to use it, but if anything goes wrong, switch to the CMake build. Note also that the Makefile cannot build the Python bindings or produce install packages.

TL;DR: Have LLVM 17 (or greater) installed and run make in the root directory of the repository (where this README is).

By default, make will use the llvm-config tool found in the PATH. If you want to use a different LLVM, such as a custom-built one following the instructions above, set the following environment variable:

$ export LLVM_CONFIG="$LLVM_ROOT/bin/llvm-config"

Now you should be able to just run make in the root directory of the Halide source tree. make run_tests will run the JIT test suite, and make test_apps will make sure all the apps compile and run (but won't check their output).

When building the tests, you can set the AOT compilation target with the HL_TARGET environment variable.

Building Halide out-of-tree with make

If you wish to build Halide in a separate directory, you can do that like so:

$ cd ..
$ mkdir halide_build
$ cd halide_build
$ make -f ../Halide/Makefile

Some useful environment variables

HL_JIT_TARGET=... will set Halide's JIT compilation target.

HL_DEBUG_CODEGEN=1 will print out pseudocode for what Halide is compiling. Higher numbers will print more detail.

HL_NUM_THREADS=... specifies the number of threads to create for the thread pool. When the async scheduling directive is used, more threads than this number may be required and thus allocated. A maximum of 256 threads is allowed. (By default, the number of cores on the host is used.)

HL_TRACE_FILE=... specifies a binary target file to dump tracing data into (ignored unless at least one trace_ feature is enabled in the target). The output can be parsed programmatically by starting from the code in utils/HalideTraceViz.cpp.

Further references

We have more documentation in doc/, the following links might be helpful:

Document Description
CMake build How to configure and build Halide using CMake.
CMake package How to use the Halide CMake package to build your code.
Hexagon How to use the Hexagon backend.
Python Documentation for the Python bindings.
RunGen How to use the RunGen interface to run and benchmark arbitrary pipelines.
Vulkan How to use the Halide Vulkan backend (BETA)
WebAssembly How to use the WebAssembly backend and how to use V8 in place of wabt.
WebGPU How to run WebGPU pipelines (BETA)

The following links are of greater interest to developers wishing to contribute code to Halide:

Document Description
CMake developer Guidelines for authoring new CMake code.
FuzzTesting Information about fuzz testing the Halide compiler (rather than pipelines). Intended for internal developers.
Testing Information about our test organization and debugging tips. Intended for internal developers.