WasmGPU.compute.kernels.axpyC64¶

Summary¶

axpyC64 computes alpha * x + y for interleaved complex64 vectors.

Syntax¶

WasmGPU.compute.kernels.axpyC64(x: StorageBuffer, y: StorageBuffer, alpha: readonly [number, number], opts?: VectorKernelOptions): StorageBuffer

Parameters¶

Name	Type	Required	Description
`x`	`StorageBuffer`	Yes	Vector multiplied by `alpha`.
`y`	`StorageBuffer`	Yes	Vector added to the scaled `x`.
`alpha`	`C64Scalar`	Yes	Complex scalar as `[real, imaginary]`.
`opts`	`VectorKernelOptions`	No	Element count, reusable output, encoder, label, and workgroup-limit validation.

Returns¶

StorageBuffer - Output containing alpha * x + y for each selected element. A newly allocated buffer enables COPY_SRC; a supplied opts.out is returned unchanged by identity.

Type Details¶

type VectorKernelOptions = {
    count?: number;
    out?: StorageBuffer;
    encoder?: GPUCommandEncoder;
    label?: string;
    validateLimits?: boolean;
};

type C64Scalar = readonly [number, number];

Each complex value is stored as adjacent [real, imaginary] f32 components. When opts.count is omitted, the input logical lengths must match and that shared length is used. Optional output buffer with at least count * 8 bytes. The output must be distinct from every input. When opts.encoder is supplied, commands are recorded but not submitted by this call.

Example¶

const wgpu = await WasmGPU.create(document.querySelector("canvas"));
const x = wgpu.compute.createStorageBuffer({ data: new Float32Array([1, 0, 2, -1, 3, 0, 4, 2]) });
const y = wgpu.compute.createStorageBuffer({ data: new Float32Array([1, 0, 2, -1, 3, 0, 4, 2]) });
const out = wgpu.compute.kernels.axpyC64(x, y, [0.5, 0]);
const values = await wgpu.compute.readback.readF32(out);
console.log(Array.from(values));