@antv/g-webgl-compute

A GPGPU implematation based on WebGL. 中文

GPGPU

You can try to solve some compute-intensive tasks like layout & particle effects with GPGPU technique. Use any rendering techniques(d3, g, Three.js or ours' rendering API if you like) when calculation is completed.

import { World } from '@antv/g-webgl-compute';

const world = new World({
  engineOptions: {
    supportCompute: true,
  },
});

const compute = world.createComputePipeline({
  shader: `
    //...
  `,
  dispatch: [1, 1, 1],
  onCompleted: (result) => {
    console.log(result); // [2, 4, 6, 8, 10, 12, 14, 16]
    world.destroy();
  },
});

// bind 2 params to Compute Shader
world.setBinding(compute, 'vectorA', [1, 2, 3, 4, 5, 6, 7, 8]);
world.setBinding(compute, 'vectorB', [1, 2, 3, 4, 5, 6, 7, 8]);

Our Compute Shader using Typescript syntax：

import { globalInvocationID } from 'g-webgpu';

@numthreads(8, 1, 1)
class Add2Vectors {
  @in @out
  vectorA: float[];

  @in
  vectorB: float[];

  sum(a: float, b: float): float {
    return a + b;
  }

  @main
  compute() {
    // 获取当前线程处理的数据
    const a = this.vectorA[globalInvocationID.x];
    const b = this.vectorB[globalInvocationID.x];

    // 输出当前线程处理完毕的数据，即两个向量相加后的结果
    this.vectorA[globalInvocationID.x] = this.sum(a, b);
  }
}

Resources

• WebGPU Design
• WebGPU Samples
• Raw WebGPU
• WebGPU implementation in Rust
• awesome-webgpu
• Matrix Compute Online Demo
• From WebGL to WebGPU
• tensorflow.js WebGPU backend
• get-started-with-gpu-compute-on-the-web

Contributing

Bootstrap with Yarn Workspace.

yarn install

Watch all the packages:

yarn watch

yarn start