AnimatedRNG/taichi

The Taichi Programming Language

The Taichi Programming Language [Details]

Chat

High-Performance Computation on Sparse Data Structures [Paper] [Video]

Differentiable Programming for Physical Simulation [Paper] [Video]

Updates

• (Oct 7, 2019) I have released experimental python 3.6 wheels on Linux (tested on Ubuntu 18.04) for those who are eager to try. More stable releases are coming in a few days. To install them:

# With GPU support (needs CUDA 9.0+)
python3 -m pip install taichi-gpu-nightly --user

# CPU only. No GPU/CUDA needed
python3 -m pip install taichi-nightly --user

Notes:

• You still need to clone this repo for demo scripts under examples/diffmpm. You do not need to execute install.py. After installation using pip you can simply go to examples/diffmpm and execute, e.g., python3 mass_spring.py 3 train.py.
• Make sure you have clang-7. On Ubuntu 18.04 you can install it with sudo apt-get install clang-7.
• Make sure you clear your legacy Taichi installation (if applicable) by cleaning the environment variables (delete TAICHI_REPO_DIR, and remove legacy taichi from PYTHONPATH) in your .bashrc or .zshrc. Or you can simply do this in your shell to temporarily clear them:

export PYTHONPATH=
export TAICHI_REPO_DIR=

(Legacy) The Taichi Library

Taichi is an open-source computer graphics library that aims to provide easy-to-use infrastructures for computer graphics R&D. It's written in C++14 and wrapped friendly with Python.

News

• May 17, 2019: Giga-Voxel SPGrid Topology Optimization Solver is released!
• March 4, 2019: MLS-MPM/CPIC solver is now MIT-licensed!
• August 14, 2018: MLS-MPM/CPIC solver reloaded! We made it closed-source for a while, which is required by anonymous peer review. It delivers 4-14x performance boost over the previous state of the art on CPUs.

Getting Started