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INSTALL.md

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Prerequisites

  • CMake

    We use cmake v3.15.1 to build Bolt. After installing the cmake, you need to set shell environment PATH to find it. You can use this simple test to confirm you have installed it successfully.

    cmake -version

  • GNU make

    We use GNU make v3.81 to build Bolt. After installing the make, you also need to set shell environment PATH. Simple test:

    make -version

  • Cross compiler

    If you plan to directly compile Bolt on ARM platform and run on ARM, you can use gcc and skip this section.

    NDK compiler uses Android NDK toolchains to build Bolt for Java APIs required by Android applications and ARM MALI GPU Bolt. GNU compiler uses gcc to build Bolt for simple ARM CPU tests. Please choose according to your scenario.

    • Android NDK compiler

      We use Android NDK android-ndk-r20 to build Bolt. After installing the Android NDK, you need to set shell environment PATH to find aarch64-linux-android21-clang++. Simple test:

      aarch64-linux-android21-clang++ --version

    • GNU compiler

      We use GNU compiler gcc-arm-8.3-2019.03-x86_64-aarch64-linux-gnu to build Bolt. You need to set shell environment PATH to find aarch64-linux-gnu-g++. Simple test:

      aarch64-linux-android21-clang++ -version

  • ADB

    We use ADB tool to transfer the executables to android mobile phones and run the program. You also need to set shell environment PATH. Simple test:

    # this will list all available android devices
adb devives

  • Optional

    • Java SDK

      If you want to compile Java programs, you need to download and install Java SE SDK. After installing the SDK, you need to set shell environment PATH to find it. Simple test:

      java --version

    • Android dx

      If you want to directly run jar file on Android device, you can use Android dx tool. We currently use Android v28.0.3 build tools. After installing the dx tool, you also need to set shell environment PATH. Simple test:

      dx --version

  • Third party library

    We provide a simple install shell script to install third party libraries(protoc, protobuf, flatbuffers, tensorflow-lite, jpeg, ARM GPU OpenCL) to the third_party directory and generate a shell script to set up compilation environment. You can choose between LLVM and GCC. Here is an example of installation for LLVM.

    ./third_party/install.sh -c llvm -t 33

Download and Build Bolt

We provide a simple shell script install.sh to build and install the Bolt library, and you can modify it according to your scenario and environment. Please refer to the options section of bolt.cmake and configure accordingly. Here we give an example of building Bolt with LLVM.

NOTE: Some build options are turned on or off by default in the given install.sh, which overwrites the settings in bolt.cmake. Be sure to check install.sh first.

git clone https://github.com/huawei-noah/bolt.git
cd bolt
./install.sh -c llvm -t 33

We will install Bolt to install_llvm directory, you will find these subdirectories in it.

  • kits

    • tinybert for intention identification

    • nmt for machine translation

    • classification for computer vision classification task

    • asr_rnnt for automatic speech recognition task RNNT model

    • asr_convolution_transformer for automatic speech recognition task Convolution+Transformer model

    • tts for text to speech

    • super_resolution for super resolution task

    • hdr for high dynamic range task

  • include

    • C API
    • Java API

  • lib: all static and shared library

  • tools

    • caffe2bolt for converting caffe model to bolt model

    • onnx2bolt for converting onnx model to bolt model

    • tflite2bolt for converting tflite model to bolt model

    • tensorflow2caffe for converting tensorflow model to caffe model

    • pytorch2caffe for converting pytorch model to caffe model

    • tensor_computing_library_search for performance tuning of the operator library

If you want to build operator and API tests, please turn on the BUILD_TEST option and rebuild Bolt. These programs will be installed to tests/bin directory.

Options

Here we list all options in bolt.cmake.

options default note
USE_CROSS_COMPILE OFF use cross compile or not
USE_GNU_GCC OFF use GNU gcc compler or not
USE_LLVM_CLANG OFF use LLVM clang compiler or not
USE_DEBUG OFF use debug information or not
USE_DYNAMIC_LIBRARY OFF use dynamic library or not
USE_CAFFE ON use caffe model as input or not
USE_ONNX ON use onnx model as input or not
USE_TFLITE ON use tflite model as input or not
USE_NEON ON use ARM NEON instruction or not
USE_FP32 OFF use FP32 implementation or not
USE_FP16 ON use FP16 implementation or not
USE_F16_MIX_PRECISION ON use ARM NEON mixed-precision (F16/F32) or not
USE_INT8 ON use INT8 implementation or not
BUILD_TEST OFF build unit test or not
USE_MALI ON use MALI GPU for parallel or not
USE_ARMV7 OFF use ARMv7 CPU or not
USE_ARMV8 ON use ARMv8 CPU or not
USE_GENERAL ON use serial CPU code for debug or not

Environment variables

We reserve some shell environment variable for Bolt.

  • Bolt_ROOT: Bolt project home directory, set by user or Bolt.
  • BOLT_MEMORY_REUSE_OPTIMIZATION: whether to use memory reuse optimization(default is ON), you can set it to OFF to disable memory reuse optimization.
  • Bolt_TensorComputing_LibraryAlgoritmMap: a path on the target device set by user to save tensor_computing library performance tuning result.

How to build Bolt MALI GPU

For compile bolt MALI GPU,

  • Ensure your ADB works well, and connected with your target device with mali gpu. NOTE: Bolt need to precompile all GPU kernels to bins on your target device, and they will be packaged to libkernelbin.a/.so If you change your target device, these kernel bins may be not adaptive, you should recompile them. Bolt support mult devices precompiling for GPU Kernels, you can connect all the target devices you need with ADB, and the kernel bins for them will be built and packged together.
  • LLVM Compiler must be used and version of andriod NDK is more than r19.
  • OpenCL headfiles and lib are provided in "/cheetah/third_party/llvm/opencl", if the OpenCL lib we provided are not matching with your target device, you can replace it with the Opencl lib on your device.
  • When you compile bolt MALI GPU, please set these options ON: USE_CROSS_COMPILE USE_LLVM_CLANG USE_FP16 USE_MALI They can be set in install.sh, options of compiler_arch llvm.
  • After open these options, run "./install.sh -c llvm -t 33" to build bolt MALI GPU