컴퓨트 진입점 디스패치

"use typeshade";

/* @example
{
  "title": "Host: dispatch a compute entry",
  "blurb": "A `@compute` entry and its host: `run()` uses the authored defaults, while `runSpecialized()` passes `{ constants }` to a direct call and to an entry inside `device.fuse()`. `WIDTH` selects the workgroup size and `GAIN` scales the output. The host calculates the group count from the selected width, keeps the plan's arrays resident, reads the result and returns the dispatch report (Rule 8.24). WebGPU and the CPU tier use 32 lanes; WebGL2 keeps the default 64 lanes and still selects `GAIN`.",
  "renderable": false,
  "reason": "missing capabilities: storageBuffer, compute"
}
*/

const WIDTH: override<u32> = 64;
const GAIN: override<f32> = 1.;

declare const k: uniform<f32>;
declare const xs: storage<array<f32>>;
declare const ys: storage<array<f32>, "read_write">;

// One invocation for each element. The entry checks its own bound, as WGSL runs it: the host
// dispatches whole workgroups of WIDTH, including a partly occupied last group.
@compute([WIDTH])
export function scale(@builtin("global_invocation_id") gid: vec3u) {
  if (gid.x >= xs.length) {
    return;
  }
  ys[gid.x] = xs[gid.x] * k * GAIN;
}

// Dispatch a `@compute` entry and read what it wrote (surface §67, Rule 8.24).
//
// The import is the shader module itself: the Vite plugin turns `scale` into a function that
// takes the entry's bindings by name, as plain values, and the number of workgroups.
import { createDevice, type FuseReport } from 'typeshade/runtime';
import 'typeshade/fuse';
import { scale } from './host-compute.shade.ts';

/** Scale `n` numbers by 2.5 on the GPU, and return them. */
export async function run(n = 259): Promise<Float32Array> {
  const xs = Float32Array.from({ length: n }, (_, i) => i);
  const ys = new Float32Array(n);
  // WIDTH defaults to 64, GAIN to 1. When the promise resolves, `ys` holds
  // what the entry wrote.
  await scale({ k: 2.5, xs, ys }, Math.ceil(n / 64));
  return ys;
}

/** Select ordinary constants in a direct call, then a workgroup size in a device plan. */
export async function runSpecialized(n = 259): Promise<{
  direct: Float32Array;
  values: Float32Array;
  report: FuseReport;
}> {
  const xs = Float32Array.from({ length: n }, (_, i) => i);
  const direct = new Float32Array(n);
  // Omitted WIDTH keeps 64. Ordinary constants work on WebGL2 too.
  await scale({ k: 2.5, xs, ys: direct }, Math.ceil(n / 64), {
    constants: { GAIN: 0.5 },
  });

  const device = await createDevice();
  try {
    // WebGL2 supports the authored workgroup shape. The other tiers can select 32 here.
    const width = device.tier === 'webgl2' ? 64 : 32;
    const input = device.array(direct);
    const output = device.array(n, 'f32');
    const report = await device.fuse(() => {
      // The group count is the caller's: selecting WIDTH does not recalculate it.
      scale({ k: 2, xs: input, ys: output }, Math.ceil(n / width), {
        constants: { WIDTH: width },
      });
    });
    // On WebGPU: one entry group, one dispatch, one submission, shape [32, 1, 1].
    // Repeating the same constants on this owner reuses its pipeline.
    return { direct, values: await output.read(), report };
  } finally {
    await device.dispose();
  }
}