[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-71492":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":11,"languages":10,"totalLinesOfCode":10,"stars":12,"forks":13,"watchers":14,"openIssues":15,"contributorsCount":16,"subscribersCount":16,"size":16,"stars1d":17,"stars7d":18,"stars30d":19,"stars90d":16,"forks30d":16,"starsTrendScore":18,"compositeScore":20,"rankGlobal":10,"rankLanguage":10,"license":21,"archived":22,"fork":22,"defaultBranch":23,"hasWiki":24,"hasPages":22,"topics":25,"createdAt":10,"pushedAt":10,"updatedAt":31,"readmeContent":32,"aiSummary":33,"trendingCount":16,"starSnapshotCount":16,"syncStatus":34,"lastSyncTime":35,"discoverSource":36},71492,"taichi","taichi-dev\u002Ftaichi","taichi-dev","Productive, portable, and performant GPU programming in Python.","https:\u002F\u002Ftaichi-lang.org",null,"C++",28244,2384,387,875,0,8,24,56,45,"Apache License 2.0",false,"master",true,[26,27,28,29,30,5],"computer-graphics","differentiable-programming","gpu","gpu-programming","sparse-computation","2026-06-12 02:02:53","\u003Cdiv align=\"center\">\n  \u003Cimg width=\"500px\" src=\"https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Ftaichi\u002Fraw\u002Fmaster\u002Fmisc\u002Flogo.png\"\u002F>\n\u003C\u002Fdiv>\n\n---\n[![Latest Release](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fv\u002Frelease\u002Ftaichi-dev\u002Ftaichi?color=blue&label=Latest%20Release)](https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Ftaichi\u002Freleases\u002Flatest)\n[![downloads](https:\u002F\u002Fpepy.tech\u002Fbadge\u002Ftaichi)](https:\u002F\u002Fpepy.tech\u002Fproject\u002Ftaichi)\n[![CI](https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Ftaichi\u002Factions\u002Fworkflows\u002Ftesting.yml\u002Fbadge.svg)](https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Ftaichi\u002Factions\u002Fworkflows\u002Ftesting.yml)\n[![Nightly Release](https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Ftaichi\u002Factions\u002Fworkflows\u002Frelease.yml\u002Fbadge.svg)](https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Ftaichi\u002Factions\u002Fworkflows\u002Frelease.yml)\n\u003Ca href=\"https:\u002F\u002Fdiscord.gg\u002Ff25GRdXRfg\">\u003Cimg alt=\"discord invitation link\" src=\"https:\u002F\u002Fdcbadge.vercel.app\u002Fapi\u002Fserver\u002Ff25GRdXRfg?style=flat\">\u003C\u002Fa>\n\n```shell\npip install taichi  # Install Taichi Lang\nti gallery          # Launch demo gallery\n```\n\n## What is Taichi Lang?\n\nTaichi Lang is an open-source, imperative, parallel programming language for high-performance numerical computation. It is embedded in Python and uses just-in-time (JIT) compiler frameworks, for example LLVM, to offload the compute-intensive Python code to the native GPU or CPU instructions.\n\n\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Ftaichi\u002Fblob\u002Fmaster\u002Fpython\u002Ftaichi\u002Fexamples\u002Fsimulation\u002Ffractal.py#L1-L31\"> \u003Cimg src=\"https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Fpublic_files\u002Fraw\u002Fmaster\u002Ftaichi\u002Ffractal_code.png\" height=\"270px\">\u003C\u002Fa>  \u003Cimg src=\"https:\u002F\u002Fraw.githubusercontent.com\u002Ftaichi-dev\u002Fpublic_files\u002Fmaster\u002Ftaichi\u002Ffractal_small.gif\" height=\"270px\">\n\nThe language has broad applications spanning real-time physical simulation, numerical computation, augmented reality, artificial intelligence, vision and robotics, visual effects in films and games, general-purpose computing, and much more.\n\n\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Ftaichi\u002Fblob\u002Fmaster\u002Fpython\u002Ftaichi\u002Fexamples\u002Fsimulation\u002Fmpm128.py\">\u003Cimg src=\"https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Fpublic_files\u002Fraw\u002Fmaster\u002Ftaichi\u002Fmpm128.gif\" height=\"192px\">\u003C\u002Fa>\n\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Fquantaichi\"> \u003Cimg src=\"https:\u002F\u002Fraw.githubusercontent.com\u002Ftaichi-dev\u002Fpublic_files\u002Fmaster\u002Ftaichi\u002Fsmoke_3d.gif\" height=\"192px\">\u003C\u002Fa>\n\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Ftaichi\u002Fblob\u002Fmaster\u002Fpython\u002Ftaichi\u002Fexamples\u002Frendering\u002Fsdf_renderer.py\">\u003Cimg src=\"https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Fpublic_files\u002Fraw\u002Fmaster\u002Ftaichi\u002Fsdf_renderer.jpg\" height=\"192px\">\u003C\u002Fa>\n\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Ftaichi\u002Fblob\u002Fmaster\u002Fpython\u002Ftaichi\u002Fexamples\u002Fsimulation\u002Feuler.py\">\u003Cimg src=\"https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Fpublic_files\u002Fraw\u002Fmaster\u002Ftaichi\u002Feuler.gif\" height=\"192px\">\u003C\u002Fa>\n\n\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Fquantaichi\">\u003Cimg src=\"https:\u002F\u002Fraw.githubusercontent.com\u002Ftaichi-dev\u002Fpublic_files\u002Fmaster\u002Ftaichi\u002Felastic_letters.gif\" height=\"213px\">\u003C\u002Fa>\n\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Fquantaichi\">\u003Cimg src=\"https:\u002F\u002Fraw.githubusercontent.com\u002Ftaichi-dev\u002Fpublic_files\u002Fmaster\u002Ftaichi\u002Ffluid_with_bunnies.gif\" height=\"213px\">\u003C\u002Fa>\n\n[...More](#demos)\n\n## Why Taichi Lang?\n\n- Built around Python: Taichi Lang shares almost the same syntax with Python, allowing you to write algorithms with minimal language barrier. It is also well integrated into the Python ecosystem, including NumPy and PyTorch.\n- Flexibility: Taichi Lang provides a set of generic data containers known as *SNode* (\u002Fˈsnoʊd\u002F), an effective mechanism for composing hierarchical, multi-dimensional fields. This can cover many use patterns in numerical simulation (e.g. [spatially sparse computing](https:\u002F\u002Fdocs.taichi-lang.org\u002Fdocs\u002Fsparse)).\n- Performance: With the `@ti.kernel` decorator, Taichi Lang's JIT compiler automatically compiles your Python functions into efficient GPU or CPU machine code for parallel execution.\n- Portability: Write your code once and run it everywhere. Currently, Taichi Lang supports most mainstream GPU APIs, such as CUDA and Vulkan.\n- ... and many more features! A cross-platform, Vulkan-based 3D visualizer, [differentiable programming](https:\u002F\u002Fdocs.taichi-lang.org\u002Fdocs\u002Fdifferentiable_programming),  [quantized computation](https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Fquantaichi) (experimental), etc.\n\n## Getting Started\n\n### Installation\n\n\u003Cdetails>\n  \u003Csummary>Prerequisites\u003C\u002Fsummary>\n\n\u003C!--TODO: Precise OS versions-->\n\n- Operating systems\n  - Windows\n  - Linux\n  - macOS\n- Python: 3.6 ~ 3.10 (64-bit only)\n- Compute backends\n  - x64\u002FARM CPUs\n  - CUDA\n  - Vulkan\n  - OpenGL (4.3+)\n  - Apple Metal\n  - WebAssembly (experiemental)\n \u003C\u002Fdetails>\n\nUse Python's package installer **pip** to install Taichi Lang:\n\n```bash\npip install --upgrade taichi\n```\n\n*We also provide a nightly package. Note that nightly packages may crash because they are not fully tested.  We cannot guarantee their validity, and you are at your own risk trying out our latest, untested features. The nightly packages can be installed from our self-hosted PyPI (Using self-hosted PyPI allows us to provide more frequent releases over a longer period of time)*\n\n```bash\npip install -i https:\u002F\u002Fpypi.taichi.graphics\u002Fsimple\u002F taichi-nightly\n```\n\n### Run your \"Hello, world!\"\n\nHere is how you can program a 2D fractal in Taichi:\n\n```py\n# python\u002Ftaichi\u002Fexamples\u002Fsimulation\u002Ffractal.py\n\nimport taichi as ti\n\nti.init(arch=ti.gpu)\n\nn = 320\npixels = ti.field(dtype=float, shape=(n * 2, n))\n\n\n@ti.func\ndef complex_sqr(z):\n    return ti.Vector([z[0]**2 - z[1]**2, z[1] * z[0] * 2])\n\n\n@ti.kernel\ndef paint(t: float):\n    for i, j in pixels:  # Parallelized over all pixels\n        c = ti.Vector([-0.8, ti.cos(t) * 0.2])\n        z = ti.Vector([i \u002F n - 1, j \u002F n - 0.5]) * 2\n        iterations = 0\n        while z.norm() \u003C 20 and iterations \u003C 50:\n            z = complex_sqr(z) + c\n            iterations += 1\n        pixels[i, j] = 1 - iterations * 0.02\n\n\ngui = ti.GUI(\"Julia Set\", res=(n * 2, n))\n\nfor i in range(1000000):\n    paint(i * 0.03)\n    gui.set_image(pixels)\n    gui.show()\n```\n\n*If Taichi Lang is properly installed, you should get the animation below 🎉:*\n\n\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Ftaichi\u002Fblob\u002Fmaster\u002Fpython\u002Ftaichi\u002Fexamples\u002Fsimulation\u002Ffractal.py#L1-L31\"> \u003C\u002Fa>\u003Cimg src=\"https:\u002F\u002Fraw.githubusercontent.com\u002Ftaichi-dev\u002Fpublic_files\u002Fmaster\u002Ftaichi\u002Ffractal_small.gif\" height=\"270px\">\n\nSee [Get started](https:\u002F\u002Fdocs.taichi-lang.org) for more information.\n\n### Build from source\n\nIf you wish to try our experimental features or build Taichi Lang for your own environments, see [Developer installation](https:\u002F\u002Fdocs.taichi-lang.org\u002Fdocs\u002Fdev_install).\n\n## Documentation\n\n- [Technical documents](https:\u002F\u002Fdocs.taichi-lang.org\u002F)\n- [API Reference](https:\u002F\u002Fdocs.taichi-lang.org\u002Fapi\u002F)\n- [Blog](https:\u002F\u002Fdocs.taichi-lang.org\u002Fblog)\n\n## Community activity [![Time period](https:\u002F\u002Fimages.repography.com\u002F32602247\u002Ftaichi-dev\u002Ftaichi\u002Frecent-activity\u002FRlhQybvihwEjfE7ngXyQR9tudBDYAvl27v-NVNMxUrg_badge.svg)](https:\u002F\u002Frepography.com)\n[![Timeline graph](https:\u002F\u002Fimages.repography.com\u002F32602247\u002Ftaichi-dev\u002Ftaichi\u002Frecent-activity\u002FRlhQybvihwEjfE7ngXyQR9tudBDYAvl27v-NVNMxUrg_timeline.svg)](https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Ftaichi\u002Fcommits)\n[![Issue status graph](https:\u002F\u002Fimages.repography.com\u002F32602247\u002Ftaichi-dev\u002Ftaichi\u002Frecent-activity\u002FRlhQybvihwEjfE7ngXyQR9tudBDYAvl27v-NVNMxUrg_issues.svg)](https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Ftaichi\u002Fissues)\n[![Pull request status graph](https:\u002F\u002Fimages.repography.com\u002F32602247\u002Ftaichi-dev\u002Ftaichi\u002Frecent-activity\u002FRlhQybvihwEjfE7ngXyQR9tudBDYAvl27v-NVNMxUrg_prs.svg)](https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Ftaichi\u002Fpulls)\n[![Trending topics](https:\u002F\u002Fimages.repography.com\u002F32602247\u002Ftaichi-dev\u002Ftaichi\u002Frecent-activity\u002FRlhQybvihwEjfE7ngXyQR9tudBDYAvl27v-NVNMxUrg_words.svg)](https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Ftaichi\u002Fcommits)\n\n## Contributing\n\nKudos to all of our amazing contributors! Taichi Lang thrives through open-source. In that spirit, we welcome all kinds of contributions from the community. If you would like to participate, check out the [Contribution Guidelines](CONTRIBUTING.md) first.\n\n\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Ftaichi\u002Fgraphs\u002Fcontributors\">\u003Cimg src=\"https:\u002F\u002Fraw.githubusercontent.com\u002Ftaichi-dev\u002Fpublic_files\u002Fmaster\u002Ftaichi\u002Fcontributors_taichi-dev_taichi_18.png\" width=\"800px\">\u003C\u002Fa>\n\n*Contributor avatars are randomly shuffled.*\n\n## License\n\nTaichi Lang is distributed under the terms of Apache License (Version 2.0).\n\nSee [Apache License](https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Ftaichi\u002Fblob\u002Fmaster\u002FLICENSE) for details.\n\n## Community\n\nFor more information about the events or community, please refer to [this page](https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Fcommunity)\n\n\n### Join our discussions\n\n- [Discord](https:\u002F\u002Fdiscord.gg\u002Ff25GRdXRfg)\n- [GitHub Discussions](https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Ftaichi\u002Fdiscussions)\n- [太极编程语言中文论坛](https:\u002F\u002Fforum.taichi.graphics\u002F)\n\n### Report an issue\n\n- If you spot an technical or documentation issue, file an issue at [GitHub Issues](https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Ftaichi\u002Fissues)\n- If you spot any security issue, mail directly to \u003Ca href = \"mailto:security@taichi.graphics?subject = Taichi Security Problem\">security@taichi.graphics\u003C\u002Fa>.\n\n### Contact us\n\n- [Discord](https:\u002F\u002Fdiscord.gg\u002Ff25GRdXRfg)\n- [WeChat](https:\u002F\u002Fforum.taichi-lang.cn\u002Ft\u002Ftopic\u002F2884)\n\n## Reference\n\n### Demos\n\n- [Nerf with Taichi](https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Ftaichi-nerfs)\n- [Taichi Lang examples](https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Ftaichi\u002Ftree\u002Fmaster\u002Fpython\u002Ftaichi\u002Fexamples)\n- [Advanced Taichi Lang examples](https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Fadvanced_examples)\n- [Awesome Taichi](https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Fawesome-taichi)\n- [DiffTaichi](https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Fdifftaichi)\n- [Taichi elements](https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Ftaichi_elements)\n- [Taichi Houdini](https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Ftaichi_houdini)\n- [More...](misc\u002Flinks.md)\n\n\n### AOT deployment\n\n- [Taichi AOT demos & tutorial](https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Ftaichi-aot-demo\u002F)\n\n\n### Lectures & talks\n\n- SIGGRAPH 2020 course on Taichi basics: [YouTube](https:\u002F\u002Fyoutu.be\u002FY0-76n3aZFA), [Bilibili](https:\u002F\u002Fwww.bilibili.com\u002Fvideo\u002FBV1kA411n7jk\u002F), [slides (pdf)](https:\u002F\u002Fyuanming.taichi.graphics\u002Fpublication\u002F2020-taichi-tutorial\u002Ftaichi-tutorial.pdf).\n- Chinagraph 2020 用太极编写物理引擎: [哔哩哔哩](https:\u002F\u002Fwww.bilibili.com\u002Fvideo\u002FBV1gA411j7H5)\n- GAMES 201 高级物理引擎实战指南 2020: [课件](https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Fgames201)\n- 太极图形课第一季：[课件](https:\u002F\u002Fgithub.com\u002FtaichiCourse01)\n- [TaichiCon](https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Ftaichicon): Taichi Developer Conferences\n- More to come...\n\n### Citations\n\nIf you use Taichi Lang in your research, please cite the corresponding papers:\n\n- [**(SIGGRAPH Asia 2019) Taichi: High-Performance Computation on Sparse Data Structures**](https:\u002F\u002Fyuanming.taichi.graphics\u002Fpublication\u002F2019-taichi\u002Ftaichi-lang.pdf) [[Video]](https:\u002F\u002Fyoutu.be\u002FwKw8LMF3Djo) [[BibTex]](https:\u002F\u002Fraw.githubusercontent.com\u002Ftaichi-dev\u002Ftaichi\u002Fmaster\u002Fmisc\u002Ftaichi_bibtex.txt) [[Code]](https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Ftaichi)\n- [**(ICLR 2020) DiffTaichi: Differentiable Programming for Physical Simulation**](https:\u002F\u002Farxiv.org\u002Fabs\u002F1910.00935) [[Video]](https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=Z1xvAZve9aE) [[BibTex]](https:\u002F\u002Fraw.githubusercontent.com\u002Ftaichi-dev\u002Ftaichi\u002Fmaster\u002Fmisc\u002Fdifftaichi_bibtex.txt) [[Code]](https:\u002F\u002Fgithub.com\u002Fyuanming-hu\u002Fdifftaichi)\n- [**(SIGGRAPH 2021) QuanTaichi: A Compiler for Quantized Simulations**](https:\u002F\u002Fyuanming.taichi.graphics\u002Fpublication\u002F2021-quantaichi\u002Fquantaichi.pdf) [[Video]](https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=0jdrAQOxJlY) [[BibTex]](https:\u002F\u002Fraw.githubusercontent.com\u002Ftaichi-dev\u002Ftaichi\u002Fmaster\u002Fmisc\u002Fquantaichi_bibtex.txt) [[Code]](https:\u002F\u002Fgithub.com\u002Ftaichi-dev\u002Fquantaichi)\n","Taichi 是一个用于高性能数值计算的开源并行编程语言，嵌入在 Python 中。它利用即时（JIT）编译器框架如 LLVM，将计算密集型的 Python 代码卸载到 GPU 或 CPU 上执行，从而实现高效能的计算。其核心功能包括支持稀疏计算、可微分编程和图形处理，特别适用于需要进行大规模并行计算的任务，比如实时物理模拟、计算机图形学、人工智能及机器人技术等领域。此外，Taichi 提供了丰富的示例库来帮助开发者快速上手，并且拥有活跃的社区支持。",2,"2026-06-11 03:38:04","high_star"]