WasmGPU.compute.dispatch1D¶

Summary¶

WasmGPU.compute.dispatch1D dispatches a linear workload by computing workgroup counts from invocations and workgroupSizeX. Use this helper for array-style kernels where each invocation maps to one logical element. Internally it calls workgroups1D and forwards to dispatch. Options control queue submission and optional device-limit validation.

Syntax¶

WasmGPU.compute.dispatch1D(pipeline: GPUComputePipeline | ComputePipeline, bindGroups: ReadonlyArray<GPUBindGroup | null | undefined>, invocations: number, workgroupSizeX: number, label?: string, opts?: ComputeDispatchOptions): GPUCommandBuffer
const commandBuffer = wgpu.compute.dispatch1D(pipeline, bindGroups, invocations, workgroupSizeX, label, opts);

Parameters¶

Name	Type	Required	Description
`pipeline`	`GPUComputePipeline \\| ComputePipeline`	Yes	Compute pipeline used for dispatch.
`bindGroups`	`ReadonlyArray<GPUBindGroup \\| null \\| undefined>`	Yes	Bind groups in pipeline layout order; nullish entries are skipped.
`invocations`	`number`	Yes	Total logical invocation count in 1D.
`workgroupSizeX`	`number`	Yes	X dimension in WGSL `@workgroup_size`.
`label`	`string`	No	Optional debug label.
`opts`	`ComputeDispatchOptions`	No	Dispatch behavior flags (`submit`, `validateLimits`).

Returns¶

GPUCommandBuffer - Encoded command buffer for the dispatch.

Type Details¶

type ComputeDispatchOptions = {
    submit?: boolean;
    validateLimits?: boolean;
};

Example¶

const canvas = document.querySelector("canvas");
const wgpu = await WasmGPU.create(canvas);

const count = 1024;
const storage = wgpu.compute.createStorageBuffer({ data: new Float32Array(count), copySrc: true });
const pipeline = wgpu.compute.createPipeline({
    code: `@group(0) @binding(0) var<storage, read_write> a: array<f32>; @compute @workgroup_size(128) fn main(@builtin(global_invocation_id) gid: vec3<u32>) { if (gid.x < ${count}u) { a[gid.x] = f32(gid.x); } }`,
    bindGroups: [{ entries: [{ binding: 0, visibility: GPUShaderStage.COMPUTE, buffer: { type: "storage" } }] }]
});
const bindGroup = pipeline.createBindGroup(0, { 0: storage });

wgpu.compute.dispatch1D(pipeline, [bindGroup], count, 128, "fill-array", { submit: true, validateLimits: true });