gpu.js

[<img width="100" alt="Logo" src="https://raw.githubusercontent.com/gpujs/gpu.js/develop/assets/jelly.png">](https://gpu.rocks/)
# GPU.js
GPU.js is a JavaScript Acceleration library for GPGPU (General purpose computing on GPUs) in JavaScript for Web and Node.
GPU.js automatically transpiles simple JavaScript functions into shader language and compiles them so they run on your GPU.
In case a GPU is not available, the functions will still run in regular JavaScript.
For some more quick concepts, see [Quick Concepts](https://github.com/gpujs/gpu.js/wiki/Quick-Concepts) on the wiki.

**New to GPU programming?** [**Learn GPGPU in your browser**](https://gpu.rocks/learn) — a free, hands-on course that teaches the subject itself, not just this library. See [Learn GPGPU](#learn-gpgpu) below.


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# What is this sorcery?

Creates a GPU accelerated kernel transpiled from a javascript function that computes a single element in the 512 x 512 matrix (2D array).
The kernel functions are ran in tandem on the GPU often resulting in very fast computations!
You can run a benchmark of this [here](https://gpu.rocks/). Typically, it will run 1-15x faster depending on your hardware.
Matrix multiplication (perform matrix multiplication on 2 matrices of size 512 x 512) written in GPU.js:

## Browser
```html
<script src="dist/gpu-browser.min.js"></script>
<script>
    // GPU is a constructor and namespace for browser
    const gpu = new GPU();
    const multiplyMatrix = gpu.createKernel(function(a, b) {
        let sum = 0;
        for (let i = 0; i < 512; i++) {
            sum += a[this.thread.y][i] * b[i][this.thread.x];
        }
        return sum;
    }).setOutput([512, 512]);

    const c = multiplyMatrix(a, b);
</script>
```

## CDN
``` 
https://unpkg.com/gpu.js@latest/dist/gpu-browser.min.js
https://cdn.jsdelivr.net/npm/gpu.js@latest/dist/gpu-browser.min.js
```

## Node
```js
const { GPU } = require('gpu.js');
const gpu = new GPU();
const multiplyMatrix = gpu.createKernel(function(a, b) {
    let sum = 0;
    for (let i = 0; i < 512; i++) {
        sum += a[this.thread.y][i] * b[i][this.thread.x];
    }
    return sum;
}).setOutput(