Developer Installation

Note this is for the compiler developers of Taichi lang. End users please use the pip packages. Supports Ubuntu 14.04/16.04/18.04, ArchLinux, Mac OS X. For NVIDIA GPU support, CUDA 9.0+ is needed. [Installing CUDA]

• Execute python3 -m pip install setuptools astpretty astor pytest opencv-python pybind11 Pillow numpy scipy GitPython yapf colorama psutil autograd
• Execute sudo apt install libtinfo-dev clang-7 on Ubuntu.
• Make sure you have LLVM 8.0.1 built from scratch, with (in the llvm source)

mkdir build
cd build
cmake .. -DLLVM_ENABLE_RTTI:BOOL=ON -DBUILD_SHARED_LIBS:BOOL=OFF -DCMAKE_BUILD_TYPE=Release -DLLVM_TARGETS_TO_BUILD="X86;NVPTX" -DLLVM_ENABLE_ASSERTIONS=ON
make -j 8
sudo make install

• Clone the taichi repo, and then

cd taichi
mkdir build
cmake ..
make -j 8

• Execute source ~/.bashrc (or source ~/.zshrc) to reload shell config.
• (Optional, if you have NVIDIA GPU) Execute ti test to run all the tests. It may take a around 20 minutes to run all tests.
• Check out examples for runnable examples. Run them with python3.

Setting up CUDA 10.1 on Ubuntu 18.04

First, make sure you have CUDA 10.1 installed. Check this by running the following command:

nvcc --version

or 

cat /usr/local/cuda/version.txt

If you dont have it - go ahead to this website and download it. These instructions were copied from the webiste above for x86_64 architecture

wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin
sudo mv cuda-ubuntu1804.pin /etc/apt/preferences.d/cuda-repository-pin-600
wget http://developer.download.nvidia.com/compute/cuda/10.1/Prod/local_installers/cuda-repo-ubuntu1804-10-1-local-10.1.243-418.87.00_1.0-1_amd64.deb
sudo dpkg -i cuda-repo-ubuntu1804-10-1-local-10.1.243-418.87.00_1.0-1_amd64.deb
sudo apt-key add /var/cuda-repo-10-1-local-10.1.243-418.87.00/7fa2af80.pub
sudo apt-get update
sudo apt-get -y install cuda 

Folder Structure

Key folders are (TODO: update)

• examples : example programs written in Taichi
  • cpp: benchmarking examples in the SIGGRAPH Asia paper (mpm_benchmark.cpp, smoke_renderer.cpp, cnn.cpp)
  • fem: the FEM benchmark
• include: language runtime
• src: the compiler implementation (The functionality is briefly documented in each file)
  • analysis: static analysis passes
  • backends: codegen to x86 and CUDA
  • transforms: IR transform passes
  • ir: the intermediate representation system
  • program: the context for taichi programs
  • ...
• test: unit tests

Troubleshooting

• Run with debug mode to see if there's any illegal memory access; (TODO: this is broken in new releases)
• Disable compiler optimizations to quickly confirm that the issue is not cause by optimization;

Bibtex

@inproceedings{hu2019taichi,
  title={Taichi: A Language for High-Performance Computation on Spatially Sparse Data Structures},
  author={Hu, Yuanming and Li, Tzu-Mao and Anderson, Luke and Ragan-Kelley, Jonathan and Durand, Fr\'edo},
  booktitle={SIGGRAPH Asia 2019 Technical Papers},
  pages={201},
  year={2019},
  organization={ACM}
}