how_to_build.md

System Requirements

HALO has been fully tested in the following development environment:

OS:

• Ubuntu 18.04

Tools and libraries:

• C++ compiler that supports C++17. (e.g. GCC >= 7.5.0)
• CMake (>= 3.14.5)
• Clang tools (>= 9.0)
• glog (>= 0.4)
• Protobuf 3.9.1

Software packages for some demos and examples:

• OpenCV 3.2.0
• Python3
• PyTorch and TensorFlow / Keras (to get pretrained model)
• ImageMagick (to preprocess test images)
• Device acceleration libraries:
  • DNNL
  • XNNPACK
  • TensorRT

NVIDIA® GPU environment:

• CUDA® (>= 10.0)
• CUDA® Deep Neural Network library™ (cuDNN) (>= 7.6.0)
• TensorRT™ (7.0.0)

Intel® GPU environment:

• Intel® oneAPI Base Toolkit

Docker Environment

For convenience, the above system requirements are also prepared and packed as a docker environment, which is under utils/docker:

• Dockerfile: contains all necessary software.
• build_image.sh: it builds two docker images:
  • CPU-only: ubuntu 18.04 based image;
  • CPU + GPU: nvidia/cuda:10.0-cudnn7-devel-ubuntu18.04 based image.
• start_docker_cpu.sh: starts the CPU-only container.
• start_docker_gpu.sh: starts the container for CPU-only and CUDA® supported environments.

You can also pull the Docker images for development from aliyun:

docker pull registry-intl.us-west-1.aliyuncs.com/computation/halo:latest-devel-cuda10.0-cudnn7-ubuntu18.04 # Ubuntu 18.04 with CUDA 10.0

docker pull registry-intl.us-west-1.aliyuncs.com/computation/halo:latest-devel-x86_64-ubuntu18.04 # Ubuntu 18.04

Build From Scratch

Get HALO

git clone https://github.com/alibaba/heterogeneity-aware-lowering-and-optimization.git --recurse-submodules -j8

Configure and Build

mkdir halo/build
cd build
cmake -DCMAKE_BUILD_TYPE=Release -G Ninja ..
ninja

Some CMAKE options:

• CMAKE_BUILD_TYPE=[Release|Debug]: select the build type.
• -DHALO_USE_GLOG=[ON]: use glob library for logging by default.
• -DHALO_CCACHE_BUILD=[ON] : enable or disable ccache for build.

Build & use Intel® GPU, please refer to Support Intel® GPU

Unit Tests

HALO uses llvm-lit test tools for unit testing. To run all unit tests, simply by

ninja check-halo