Build support status

Host build

• Windows build (cpu and gpu)
• Linux build (cpu and gpu)
• MacOS build (cpu only)
• Android build (cpu only) at termux env

Cross build

• Windows cross build ARM-Android (ok)
• Windows cross build ARM-Linux (ok)
• Linux cross build ARM-Android (ok)
• Linux cross build ARM-Linux (ok)
• Linux cross build RISCV(support rvv)-Linux (ok)
• MacOS cross build ARM-Android (ok)
• MacOS cross build ARM-Linux (ok but experimental)
• MacOS cross build IOS (ok)

Build env prepare

Prerequisites

Most of the dependencies of MegBrain(MegEngine) are located in third_party directory, which can be prepared by executing:

./third_party/prepare.sh
./third_party/install-mkl.sh

Windows shell env(bash from windows-git), infact if you can use git command on Windows, which means you always install bash.exe at the same dir of git.exe, find it, then you can prepare third-party code by

• command:

bash.exe ./third_party/prepare.sh
bash.exe ./third_party/install-mkl.sh
if you are use github MegEngine and build for Windows XP, please
	1: donwload mkl for xp from: http://registrationcenter-download.intel.com/akdlm/irc_nas/4617/w_mkl_11.1.4.237.exe
	2: install exe, then from install dir:
		2a: cp include file to third_party/mkl/x86_32/include/
		2b: cp lib file to third_party/mkl/x86_32/lib/

About third_party/prepare.sh, also support to be managed by CMake, just config EXTRA_CMAKE_ARGS="-DMGE_SYNC_THIRD_PARTY=ON" before run scripts/cmake-build/*.sh

But some dependencies need to be installed manually:

• CUDA(>=10.1), cuDNN(>=7.6) are required when building MegBrain with CUDA support.
• TensorRT(>=5.1.5) is required when building with TensorRT support.
• LLVM/Clang(>=6.0) is required when building with Halide JIT support.
• Python(>=3.6) and numpy are required to build Python modules.

Package install

Windows host build

• commands:

0: about all windows config
    * please check scripts/whl/windows/config.sh
1: install git (Windows GUI)
	* download git-install.exe from https://github.com/git-for-windows/git/releases
	* NOTICE: We find some version, which bigger than v2.35 may report: Bad address issue when run cmd.exe /C "dir", so we suggest install v2.34
	* only need choose git-lfs component
	* install to default dir:  /c/Program\ Files/Git
2: install cuda components (Windows GUI) if you want to build with CUDA
    * download cuda/cudnn/trt from NVIDIA or by scripts/whl/windows/cuda_cudnn_install.py
    * export CUDA_ROOT_DIR/CUDNN_ROOT_DIR/TRT_ROOT_DIR to real cuda/cudnn/trt location
3: install all env except cuda env
    * just run scripts/whl/windows/env_prepare.sh
4: edit system env variables (Windows GUI)
	* append "Path" env value
        C:\Program Files\Git\cmd
		C:\Users\build\megengine_dev_tools\pyenv-win\pyenv-win\versions\3.10.1
        change `build` to your real user name

Linux host build

• commands:

0: we provide Dockerfile if you do not prepare local env
    * check about scripts/whl/manylinux2014/build_image.sh
1: install Cmake, which version >= 3.15.2, ninja-build
2: install gcc/g++, which version >= 6, (gcc/g++ >= 7, if need build training mode)
3: install build-essential git git-lfs gfortran libgfortran-6-dev autoconf gnupg flex bison gperf curl zlib1g-dev gcc-multilib g++-multilib lib32ncurses5-dev libxml2-utils xsltproc unzip libtool librdmacm-dev rdmacm-utils python3-dev python3-numpy texinfo
4: CUDA env(if build with CUDA), please export CUDA/CUDNN/TRT env, for example:
export CUDA_ROOT_DIR=/path/to/cuda
export CUDNN_ROOT_DIR=/path/to/cudnn
export TRT_ROOT_DIR=/path/to/tensorrt

MacOS host build

• commands:

1: install Cmake, which version >= 3.15.2
2: install brew: /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install.sh)"
3: brew install python python3 coreutils ninja
4: install at least xcode command line tool: https://developer.apple.com/xcode/
5: about cuda: we do not support CUDA on MacOS
6: python3 -m pip install numpy (if you want to build with training mode)

Cross build for ARM-Android

Now we support Windows/Linux/MacOS cross build to ARM-Android

• commands:

2: download NDK from https://developer.android.google.cn/ndk/downloads/ for diff OS platform package, suggested NDK20 or NDK21
3: export NDK_ROOT=NDK_DIR at bash-like env

Cross build for ARM-Linux

Now we support ARM-Linux on Linux and Windows fully, also experimental on MacOS

• commands:

1: download toolchains from http://releases.linaro.org/components/toolchain/binaries/ or https://developer.arm.com/tools-and-software/open-source-software/developer-tools/gnu-toolchain/gnu-a/downloads if use Windows or Linux
2: download toolchains from https://github.com/thinkski/osx-arm-linux-toolchains if use MacOS

Cross build for RISCV-Linux

Now we support RISCV-Linux

• commands:

1: download toolchains from https://github.com/riscv-collab/riscv-gnu-toolchain

Cross build for IOS

Now we only support cross build to IOS from MACOS

• commands:

1: install full xcode: https://developer.apple.com/xcode/

How to build

With bash env(Linux/MacOS/Windows-git-bash)

• host build just use scripts:scripts/cmake-build/host_build.sh builds MegBrain(MegEngine) that runs on the same host machine (i.e., no cross compiling) The following command displays the usage:

  scripts/cmake-build/host_build.sh -h
    more example:
    1a: build for Windows for XP (sp3): (dbg) EXTRA_CMAKE_ARGS="-DMGE_DEPLOY_INFERENCE_ON_WINDOWS_XP=ON" ./scripts/cmake-build/host_build.sh -m -d
                                        (opt) EXTRA_CMAKE_ARGS="-DMGE_DEPLOY_INFERENCE_ON_WINDOWS_XP=ON" ./scripts/cmake-build/host_build.sh -m
    2a: build for Windows for XP (sp2): (dbg) EXTRA_CMAKE_ARGS="-DMGE_DEPLOY_INFERENCE_ON_WINDOWS_XP_SP2=ON" ./scripts/cmake-build/host_build.sh -m -d
                                        (opt) EXTRA_CMAKE_ARGS="-DMGE_DEPLOY_INFERENCE_ON_WINDOWS_XP_SP2=ON" ./scripts/cmake-build/host_build.sh -m

• cross build to ARM-Android: scripts/cmake-build/cross_build_android_arm_inference.sh builds MegBrain(MegEngine) for inference on Android-ARM platforms. The following command displays the usage:

  scripts/cmake-build/cross_build_android_arm_inference.sh -h

• cross build to ARM-Linux: scripts/cmake-build/cross_build_linux_arm_inference.sh builds MegBrain(MegEngine) for inference on Linux-ARM platforms. The following command displays the usage:

  scripts/cmake-build/cross_build_linux_arm_inference.sh -h

• cross build to RISCV-Linux: scripts/cmake-build/cross_build_linux_riscv_inference.sh builds MegBrain(MegEngine) for inference on Linux-RISCV platforms. The following command displays the usage:

  scripts/cmake-build/cross_build_linux_riscv_inference.sh -h
  • if board support RVV(at least 0.7), for example: nezha D1 , use -a rv64gcv0p7
  • if board do not support RVV, use -a rv64norvv

• cross build to IOS: scripts/cmake-build/cross_build_ios_arm_inference.sh builds MegBrain(MegEngine) for inference on iOS (iPhone/iPad) platforms. The following command displays the usage:

  scripts/cmake-build/cross_build_ios_arm_inference.sh -h

Visual Studio GUI(only for Windows host)

• command:

1: import megengine src to Visual Studio as a project
2: right click CMakeLists.txt, choose config 'cmake config' choose clang_cl_x86 or clang_cl_x64
3: config other CMAKE config, eg, CUDA ON OR OFF

Other ARM-Linux-Like board support

It's easy to support other customized arm-linux-like board, example:

• 1: HISI 3516/3519, infact u can just use toolchains from arm developer or linaro then call scripts/cmake-build/cross_build_linux_arm_inference.sh to build a ELF binary, or if you get HISI official toolschain, you just need modify CMAKE_CXX_COMPILER and CMAKE_C_COMPILER in toolchains/arm-linux-gnueabi* to a real name

• 2: about Raspberry, just use scripts/cmake-build/cross_build_linux_arm_inference.sh

About build args

All scripts/cmake-build/*.sh support EXTRA_CMAKE_ARGS to config more options

• get support options by -l, for example: scripts/cmake-build/cross_build_android_arm_inference.sh -l
• CMake support Release, Debug, RelWithDebInfo build type, all scripts/cmake-build/*.sh default build type is Release, can build Debug type with -d, if you want to build with RelWithDebInfo, you can config with EXTRA_CMAKE_ARGS, for example: EXTRA_CMAKE_ARGS="-DCMAKE_BUILD_TYPE=RelWithDebInfo" ./scripts/cmake-build/host_build.sh, Notice: when build with Release , we will disable some build components: RTTI, MGB_ASSERT_LOC, and MGB_ENABLE_DEBUG_UTIL
• CMake build all targets by default, if you just want build a specified target, you can build with -e xxxx , for example, only build with lite_shared : ./scripts/cmake-build/cross_build_android_arm_inference.sh -e lite_shared , Notice: when with -e, will do not strip target, always for debug or need strip target manually
• About others build flag, please run with flag -h