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pip install taichi # Install Taichi Lang
ti gallery # Launch demo gallery
Taichi 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.
The 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.
@ti.kernel
decorator, Taichi Lang's JIT compiler automatically compiles your Python functions into efficient GPU or CPU machine code for parallel execution.Use Python's package installer pip to install Taichi Lang:
pip install --upgrade taichi
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)
pip install -i https://pypi.taichi.graphics/simple/ taichi-nightly
Here is how you can program a 2D fractal in Taichi:
# python/taichi/examples/simulation/fractal.py
import taichi as ti
ti.init(arch=ti.gpu)
n = 320
pixels = ti.field(dtype=float, shape=(n * 2, n))
@ti.func
def complex_sqr(z):
return ti.Vector([z[0]**2 - z[1]**2, z[1] * z[0] * 2])
@ti.kernel
def paint(t: float):
for i, j in pixels: # Parallelized over all pixels
c = ti.Vector([-0.8, ti.cos(t) * 0.2])
z = ti.Vector([i / n - 1, j / n - 0.5]) * 2
iterations = 0
while z.norm() < 20 and iterations < 50:
z = complex_sqr(z) + c
iterations += 1
pixels[i, j] = 1 - iterations * 0.02
gui = ti.GUI("Julia Set", res=(n * 2, n))
for i in range(1000000):
paint(i * 0.03)
gui.set_image(pixels)
gui.show()
If Taichi Lang is properly installed, you should get the animation below 🎉:
See Get started for more information.
If you wish to try our our experimental features or build Taichi Lang for your own environments, see Developer installation.
Kudos 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 first.
Contributor avatars are randomly shuffled.
Taichi Lang is distributed under the terms of Apache License (Version 2.0).
See Apache License for details.
Voxel Challenge 2022 is open for submissions until 18th May. Find out more here.
If you use Taichi Lang in your research, please cite the corresponding papers:
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