taichi

Introduction to Taichi Lang

What is Taichi Lang?

Taichi Lang is an open-source programming language designed for high-performance numerical computations. It is unique because it is embedded in Python, which means you can write your code in Python while Taichi compiles the compute-intensive parts to run efficiently on GPUs or CPUs. This is achieved through just-in-time (JIT) compilation, using frameworks like LLVM, which translates your Python code into native instructions that can be executed in parallel.

Applications

Taichi Lang is versatile and finds use in various fields. It is particularly beneficial in scenarios that demand real-time physical simulations and numerical computations. This includes augmented reality, artificial intelligence, robotics, computer vision, and visual effects in movies and games. Its capabilities also extend to general-purpose computation and are adaptable for a wide range of complex simulations and renderings.

Why Choose Taichi Lang?

• Python Compatibility: Taichi Lang closely resembles Python's syntax, which makes it accessible and easy for Python programmers to adopt. It seamlessly integrates with the Python ecosystem, including popular libraries like NumPy and PyTorch.
• Flexibility: It offers flexible data structures known as SNode, which are designed to handle complex, multi-dimensional fields. This is particularly beneficial for simulations that involve spatially sparse computing.
• Performance: By using the @ti.kernel decorator in your code, Taichi's JIT compiler will automatically transform Python functions into optimized GPU or CPU machine code, taking full advantage of parallel processing.
• Portability: You can write your code once and execute it across different platforms, as Taichi supports various mainstream GPU APIs such as CUDA and Vulkan, among others.

Getting Started

Installation

Installing Taichi Lang is straightforward with Python's package installer, pip:

pip install --upgrade taichi

For those interested in exploring the cutting-edge features that are not yet fully tested, there is an option to install the nightly version:

pip install -i https://pypi.taichi.graphics/simple/ taichi-nightly

Hello World

Here’s a simple example of how to create a 2D fractal:

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:
        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()

This program uses Taichi to render a smooth fractal pattern, demonstrating how simple and efficient numerical simulation can be using Taichi Lang.

Community and Contributing

Taichi Lang is powered by its open-source community, and contributions from developers worldwide have been instrumental in its development. Anyone interested in contributing is encouraged to check the contribution guidelines.

Conclusion

Taichi Lang is a powerful tool for those seeking to develop high-performance simulations and computational tasks efficiently. Its integration with Python, flexibility, and ability to leverage GPU and CPU power makes it an attractive option for professionals in numerous tech fields. Whether you are new to numerical computation or an experienced programmer looking to optimize your code, Taichi Lang offers promising capabilities and a welcoming community to explore.