taichidev/taichi repository overview

⁠ Tutorial ⁠ | Examples ⁠ | Forum ⁠

⁠ Documentation ⁠ | 简体中文文档 ⁠ | Contributor Guidelines ⁠

⁠Overview

Taichi (太极) is a programming language designed for high-performance computer graphics. It is deeply embedded in Python, and its just-in-time compiler offloads compute-intensive tasks to multi-core CPUs and massively parallel GPUs.

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Advanced features of Taichi include spatially sparse computing⁠ and differentiable programming⁠ [examples]⁠.

Please check out our SIGGRAPH 2020 course on Taichi basics: YouTube⁠, Bilibili⁠, slides (pdf)⁠.

中文视频教程: [哔哩哔哩]⁠, [幻灯片]⁠

⁠Examples (More...⁠)

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⁠Installation

python3 -m pip install taichi

Supported OS: Windows, Linux, Mac OS X; Python: 3.6/3.7/3.8 (64-bit only)/3.9 (64-bit only); Backends: x64 CPUs, CUDA, Apple Metal, OpenGL Compute Shaders.

Please build from source for other configurations (e.g., your CPU is ARM, or you want to try out our experimental C backend).

Note:

• The PyPI package supports x64 CPU, CUDA 10/11, Metal, and OpenGL Compute Shader backends.
• On Ubuntu 19.04+, please sudo apt install libtinfo5.
• On Windows, please install Microsoft Visual C++ Redistributable⁠ if you haven't.
• [All releases]⁠

	Linux (CUDA)	OS X (10.14+)	Windows	Documentation
Build
PyPI

⁠Contributors

We welcome feedback and comments. If you would like to contribute to Taichi, please check out our Contributor Guidelines⁠.

If you use Taichi in your research, please cite our papers:

• (SIGGRAPH Asia 2019) Taichi: High-Performance Computation on Sparse Data Structures⁠ [Video]⁠ [BibTex]⁠ [Code]⁠
• (ICLR 2020) DiffTaichi: Differentiable Programming for Physical Simulation⁠ [Video]⁠ [BibTex]⁠ [Code]⁠

⁠Links

• Taichi Conference⁠: Taichi developer conferences.
• GAMES 201 Lectures⁠: (Chinese) A hands-on course on building advanced physics engines, based on Taichi.
• More...⁠

⁠Security

Please disclose security issues responsibly by contacting [email protected]⁠.