taichi

The Taichi Programming Language

These details have not been verified by PyPI

Project links

Homepage

GitHub Statistics

View statistics for this project via Libraries.io, or by using our public dataset on Google BigQuery

Project description

Tutorial | Examples | Forum

Documentation | 简体中文文档 | Contributor Guidelines

Overview

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

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

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...)

Installation

python3 -m pip install taichi

Supported OS: Windows, Linux, Mac OS X; Python: 3.6-3.9 (64-bit only); Backends: x64 CPUs, CUDA, Apple Metal, Vulkan, 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, Vulkan and OpenGL Compute Shader backends.
On Windows, please install Microsoft Visual C++ Redistributable if you haven't.
[All releases]

Contributing

We'd love to hear your comments or any of your feedback! If you would like to contribute to Taichi, please check out the Contribution Guidelines first.

Contributors

Note: contributor avatars above are randomly shuffled.

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

Security

Please disclose security issues responsibly to security@taichi.graphics.

1. TaichiZoo is still in its Beta version. If you've encountered any issue, please do not hesitate to file a bug.

Project details

These details have not been verified by PyPI

Project links

Homepage

GitHub Statistics

View statistics for this project via Libraries.io, or by using our public dataset on Google BigQuery

Release history Release notifications | RSS feed

1.7.1

Apr 17, 2024

1.7.0

Nov 27, 2023

1.6.0

May 12, 2023

1.5.0

Mar 27, 2023

1.4.1

Feb 2, 2023

1.4.0

Jan 16, 2023

1.3.0

Nov 30, 2022

1.2.2

Nov 15, 2022

1.2.1

Nov 1, 2022

1.2.0

Oct 25, 2022

1.1.3

Sep 20, 2022

1.1.2

Aug 18, 2022

1.1.1 yanked

Aug 18, 2022

Reason this release was yanked:

Wrong version number

1.1.0

Aug 10, 2022

1.0.4

Jul 12, 2022

1.0.3

Jun 13, 2022

1.0.2

May 18, 2022

1.0.1

Apr 27, 2022

1.0.0

Apr 13, 2022

0.9.2

Mar 23, 2022

0.9.1

Mar 8, 2022

0.9.0

Feb 22, 2022

0.8.11

Jan 25, 2022

0.8.10

Jan 18, 2022

0.8.9

Jan 4, 2022

0.8.8

Dec 21, 2021

This version

0.8.7

Dec 7, 2021

0.8.6 yanked

Nov 23, 2021

Reason this release was yanked:

taichi 0.8.6 is buggy

0.8.5

Nov 10, 2021

0.8.4

Oct 27, 2021

0.8.3

Oct 14, 2021

0.8.2

Oct 12, 2021

0.8.1

Sep 29, 2021

0.8.0

Sep 23, 2021

0.7.32

Sep 9, 2021

0.7.31

Sep 2, 2021

0.7.30

Aug 25, 2021

0.7.29

Aug 12, 2021

0.7.28 yanked

Aug 3, 2021

Reason this release was yanked:

https://github.com/taichi-dev/taichi/issues/2642

0.7.26

Jul 12, 2021

0.7.25

Jul 2, 2021

0.7.24

Jun 28, 2021

0.7.23

Jun 24, 2021

0.7.22

Jun 21, 2021

0.7.21

Jun 7, 2021

0.7.20

May 20, 2021

0.7.19

May 13, 2021

0.7.18

May 1, 2021

0.7.17

Apr 25, 2021

0.7.16

Apr 13, 2021

0.7.15

Mar 14, 2021

0.7.14

Feb 13, 2021

0.7.13

Feb 4, 2021

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

taichi-0.8.7-cp39-cp39-win_amd64.whl (21.7 MB view hashes)

Uploaded Dec 7, 2021 CPython 3.9 Windows x86-64

taichi-0.8.7-cp39-cp39-manylinux1_x86_64.whl (27.1 MB view hashes)

Uploaded Dec 7, 2021 CPython 3.9

taichi-0.8.7-cp39-cp39-macosx_11_0_arm64.whl (20.3 MB view hashes)

Uploaded Dec 7, 2021 CPython 3.9 macOS 11.0+ ARM64

taichi-0.8.7-cp39-cp39-macosx_10_15_x86_64.whl (24.4 MB view hashes)

Uploaded Dec 7, 2021 CPython 3.9 macOS 10.15+ x86-64

taichi-0.8.7-cp39-cp39-macosx_10_14_x86_64.whl (23.5 MB view hashes)

Uploaded Dec 7, 2021 CPython 3.9 macOS 10.14+ x86-64

taichi-0.8.7-cp38-cp38-win_amd64.whl (21.7 MB view hashes)

Uploaded Dec 7, 2021 CPython 3.8 Windows x86-64

taichi-0.8.7-cp38-cp38-manylinux1_x86_64.whl (27.1 MB view hashes)

Uploaded Dec 7, 2021 CPython 3.8

taichi-0.8.7-cp38-cp38-macosx_11_0_arm64.whl (20.3 MB view hashes)

Uploaded Dec 7, 2021 CPython 3.8 macOS 11.0+ ARM64

taichi-0.8.7-cp38-cp38-macosx_10_15_x86_64.whl (24.4 MB view hashes)

Uploaded Dec 7, 2021 CPython 3.8 macOS 10.15+ x86-64

taichi-0.8.7-cp38-cp38-macosx_10_14_x86_64.whl (23.5 MB view hashes)

Uploaded Dec 7, 2021 CPython 3.8 macOS 10.14+ x86-64

taichi-0.8.7-cp37-cp37m-win_amd64.whl (21.7 MB view hashes)

Uploaded Dec 7, 2021 CPython 3.7m Windows x86-64

taichi-0.8.7-cp37-cp37m-manylinux1_x86_64.whl (27.0 MB view hashes)

Uploaded Dec 7, 2021 CPython 3.7m

taichi-0.8.7-cp37-cp37m-macosx_10_15_x86_64.whl (24.3 MB view hashes)

Uploaded Dec 7, 2021 CPython 3.7m macOS 10.15+ x86-64

taichi-0.8.7-cp37-cp37m-macosx_10_14_x86_64.whl (23.5 MB view hashes)

Uploaded Dec 7, 2021 CPython 3.7m macOS 10.14+ x86-64

taichi-0.8.7-cp36-cp36m-win_amd64.whl (21.7 MB view hashes)

Uploaded Dec 7, 2021 CPython 3.6m Windows x86-64

taichi-0.8.7-cp36-cp36m-manylinux1_x86_64.whl (27.0 MB view hashes)

Uploaded Dec 7, 2021 CPython 3.6m

taichi-0.8.7-cp36-cp36m-macosx_10_15_x86_64.whl (24.3 MB view hashes)

Uploaded Dec 7, 2021 CPython 3.6m macOS 10.15+ x86-64

taichi-0.8.7-cp36-cp36m-macosx_10_14_x86_64.whl (23.5 MB view hashes)

Uploaded Dec 7, 2021 CPython 3.6m macOS 10.14+ x86-64

Hashes for taichi-0.8.7-cp39-cp39-win_amd64.whl

Hashes for taichi-0.8.7-cp39-cp39-win_amd64.whl
Algorithm	Hash digest
SHA256	`18dd9168699db88c4e125e23718a558b0f3e835c8c45154da06bd0a854fdd97d`
MD5	`cdb8a3f7704a716f55d468aba493d7ce`
BLAKE2b-256	`9ad33532d5f7b4a14d16c38506294cde06e372318f30a66bc6ee18dce1e27846`

Hashes for taichi-0.8.7-cp39-cp39-manylinux1_x86_64.whl

Hashes for taichi-0.8.7-cp39-cp39-manylinux1_x86_64.whl
Algorithm	Hash digest
SHA256	`8c0db1985a7061b5639640642587dcaf3b8074eb3bbecd8263c403cf3ff0a7e9`
MD5	`c18c424f30af00a255df0af815f316d0`
BLAKE2b-256	`b2d24cc808ebdd67ecf2062c28137a65742bc34832d6f8147e95931f9be87b51`

Hashes for taichi-0.8.7-cp39-cp39-macosx_11_0_arm64.whl

Hashes for taichi-0.8.7-cp39-cp39-macosx_11_0_arm64.whl
Algorithm	Hash digest
SHA256	`33ac9e5e7ece7dc8052649630bdf11fed8a8831fb50245d14486e58356d97e1e`
MD5	`f54a2993f477c72504490ee2ed24fb90`
BLAKE2b-256	`f890c936f3323a181a42eb1c9b98cdc01263333d40850905686e003ce54a6c21`

Hashes for taichi-0.8.7-cp39-cp39-macosx_10_15_x86_64.whl

Hashes for taichi-0.8.7-cp39-cp39-macosx_10_15_x86_64.whl
Algorithm	Hash digest
SHA256	`da731aee09c741d1b4c3f1b2d2353f717eb947bf5a8f5d4a4d8904727583b776`
MD5	`a917cbbcc0e506dcaf72e46a5a853e6f`
BLAKE2b-256	`f82bdc78ec77c320d93df02c4f4758d21f925b1f0e709b913e420c47363a6170`

Hashes for taichi-0.8.7-cp39-cp39-macosx_10_14_x86_64.whl

Hashes for taichi-0.8.7-cp39-cp39-macosx_10_14_x86_64.whl
Algorithm	Hash digest
SHA256	`9af4f61f9474423cf166c91b8bad6a49f5ee1a76ca42ff02bf23d884283fbb36`
MD5	`8be82ce148fd3347349a27b47fc5b317`
BLAKE2b-256	`dca3fefbaa5fb8de9428675a694fae528d1ca8ad227122361333c143efa7a56e`

Hashes for taichi-0.8.7-cp38-cp38-win_amd64.whl

Hashes for taichi-0.8.7-cp38-cp38-win_amd64.whl
Algorithm	Hash digest
SHA256	`161413ae177f9fefc6a93f8dfcc83ac1302b24f30ae4d5e5a9075690ab215176`
MD5	`254b433d2ba3938cbd191c8b63534e7c`
BLAKE2b-256	`cbd5a90ad794f8c3ea543788aff1a5ec91abb38f7c061409f32e55986315e4cd`

Hashes for taichi-0.8.7-cp38-cp38-manylinux1_x86_64.whl

Hashes for taichi-0.8.7-cp38-cp38-manylinux1_x86_64.whl
Algorithm	Hash digest
SHA256	`9685ecf3e79dcdb7fbb55c1f3abe0cc70742b1975039e3fca0416f5d9f047d90`
MD5	`57f8cd06003b08d2a151fbb0fe0ab1a8`
BLAKE2b-256	`15555380be7d458f37c54a6700e4a60f405936bc1f58d0cafd3a3b196a0219dd`

Hashes for taichi-0.8.7-cp38-cp38-macosx_11_0_arm64.whl

Hashes for taichi-0.8.7-cp38-cp38-macosx_11_0_arm64.whl
Algorithm	Hash digest
SHA256	`7749de5ce4642fac865cce2fca625d052449522c7fba2e531c71791b69486d9a`
MD5	`fe62151828aaec73a31d7e7a9b7bd528`
BLAKE2b-256	`8a66a08dc00c4b109eab209de4216bb0875c3c517214e1b9294bde001d592ad1`

Hashes for taichi-0.8.7-cp38-cp38-macosx_10_15_x86_64.whl

Hashes for taichi-0.8.7-cp38-cp38-macosx_10_15_x86_64.whl
Algorithm	Hash digest
SHA256	`0514ebccdb0ffd2c7a2fea63e8264deba290190017849a132b1e89ee0bde6fad`
MD5	`5f6a2cfd3bfc8641df28df156e152884`
BLAKE2b-256	`88f04555abbb2ac8b8abc7f45ee3139d39d4814ce21ee7f8b35ea317b5de97e1`

Hashes for taichi-0.8.7-cp38-cp38-macosx_10_14_x86_64.whl

Hashes for taichi-0.8.7-cp38-cp38-macosx_10_14_x86_64.whl
Algorithm	Hash digest
SHA256	`a0f2aa64a35aa4c4ecd5f74b0a17eddb220389ae3286b0412a77d9442717661c`
MD5	`6921469f0fb5f283adda509a72535310`
BLAKE2b-256	`89ab23063577b676d3ebdb050211cf7ad8eb5af14c9838c229737f8e81280d36`

Hashes for taichi-0.8.7-cp37-cp37m-win_amd64.whl

Hashes for taichi-0.8.7-cp37-cp37m-win_amd64.whl
Algorithm	Hash digest
SHA256	`bb2fb2d44517b498964bb3dc083447e6a36ebebed12d375c6fa044f607c4018f`
MD5	`8083cd06c6dac2f69d1142c3aa7e7785`
BLAKE2b-256	`8a2a7a1706efd8c36d8d9bb3009e008d85df4bd86d262cd85c4a4c397af4fef4`

Hashes for taichi-0.8.7-cp37-cp37m-manylinux1_x86_64.whl

Hashes for taichi-0.8.7-cp37-cp37m-manylinux1_x86_64.whl
Algorithm	Hash digest
SHA256	`7eddcfbf65f767675f2d1f95eb908681126195fe1948f504db9622c842578547`
MD5	`11a068b0c088b1a9775eef4be5047b9e`
BLAKE2b-256	`d36c253cac44ed4e27868f8d8a28f9d980a2d63b9f1c45716783290a4f983d58`

Hashes for taichi-0.8.7-cp37-cp37m-macosx_10_15_x86_64.whl

Hashes for taichi-0.8.7-cp37-cp37m-macosx_10_15_x86_64.whl
Algorithm	Hash digest
SHA256	`eb532924725684d5afe2828c0e4210bf580d028af7575703cfc326730f5af71a`
MD5	`6f818b85816365ba20583eab255a066d`
BLAKE2b-256	`af896b14f172ce09fcbcb5f9b7ea02cccbc7221d18046d2b4bbc6e5a9626527d`

Hashes for taichi-0.8.7-cp37-cp37m-macosx_10_14_x86_64.whl

Hashes for taichi-0.8.7-cp37-cp37m-macosx_10_14_x86_64.whl
Algorithm	Hash digest
SHA256	`fbf99bba6aae3bd4d9b0d2fa5126703b6911201cd49bc9fb7baaf6809767a9af`
MD5	`c3d29f698148d7632a87712aa0f86b0e`
BLAKE2b-256	`2c4eb273fb240792550e94d669cb0ddc3f75d80a5da87506ca796a585ef2eff5`

Hashes for taichi-0.8.7-cp36-cp36m-win_amd64.whl

Hashes for taichi-0.8.7-cp36-cp36m-win_amd64.whl
Algorithm	Hash digest
SHA256	`661290c6b6f80aa17e2adae6726384db9b1a710d9d838f20d9a7b8aa4c5f022e`
MD5	`88645ffb387eaab7e3411f26cab2222e`
BLAKE2b-256	`d113a85bb110a3e388ce0b6da47c3715e2632f31875a7d6eea001d07c2064ed3`

Hashes for taichi-0.8.7-cp36-cp36m-manylinux1_x86_64.whl

Hashes for taichi-0.8.7-cp36-cp36m-manylinux1_x86_64.whl
Algorithm	Hash digest
SHA256	`4631e11d7853a44c0f98124afdae6715b5fb01d5ca295065c0c5de9911945041`
MD5	`64e10e32694ae2d657e8fb1b669a8e46`
BLAKE2b-256	`c186a508329a410103a149aa0c4a145a763715659658f0372e215590c6de355c`

Hashes for taichi-0.8.7-cp36-cp36m-macosx_10_15_x86_64.whl

Hashes for taichi-0.8.7-cp36-cp36m-macosx_10_15_x86_64.whl
Algorithm	Hash digest
SHA256	`5f1a9e2972db74bef5149e2f19193c954f9bb0b7c19efef2783562df248df894`
MD5	`19b334d933c0a8eda3d966ec34bd06bd`
BLAKE2b-256	`e0e626e3df9536a98cceeaf35791ce7307b1e8a89260cb91d01aecb2d83f0561`

Hashes for taichi-0.8.7-cp36-cp36m-macosx_10_14_x86_64.whl

Hashes for taichi-0.8.7-cp36-cp36m-macosx_10_14_x86_64.whl
Algorithm	Hash digest
SHA256	`6c4729dc585cae1dc72284c2901ac9116a41cec88f27af3bc1f8106636eb9b07`
MD5	`356298baa8e8870fef8be8e2df54a02f`
BLAKE2b-256	`57d106a52967033d8959e029b535721453a3525c398cd79f67b12978f0811086`