Vue是當前非常熱門的前端框架之一，越來越多的開發(fā)者選擇使用Vue來構建高質量的Web應用程序。當涉及到前端數(shù)據(jù)可視化和復雜計算時，需要一個強大的計算引擎來支持框架的運行。

GPU計算是一種能夠快速進行復雜計算的方法。通常我們會使用CUDA編寫GPU計算代碼，而在Vue中，由于其支持SSR，所以存在一些特殊的編譯要求。

// 利用GPU實現(xiàn)向四個方向的模糊濾鏡算法
export default {
methods: {
async gaussianBlur(imageData, radius) {
const canvas = document.createElement('canvas')
const context = canvas.getContext('2d')
const { width, height } = imageData
canvas.width = width
canvas.height = height
context.putImageData(imageData, 0, 0)
const pixels = context.getImageData(0, 0, width, height)
const gpu = new GPU({
mode: 'gpu',
})
const kernel = gpu.createKernel(function (pixels, rowCount, columnCount, radius) {
const imageData = pixels[this.thread.y][this.thread.x]
const i = this.thread.x + rowCount * this.thread.y
const totalWeight = (radius * 2 + 1) ** 2
let rTotal = 0
let gTotal = 0
let bTotal = 0
let currentRadius = 0
for (let y = -radius; y< radius + 1; y++) {
for (let x = -radius; x< radius + 1; x++) {
const rowOffset = x + this.thread.y
const columnOffset = y + this.thread.x
const pixelIndex = rowOffset * rowCount + columnOffset
if (
rowOffset >-1 &&
columnOffset >-1 &&
rowOffset< columnCount &&
columnOffset< rowCount
) {
currentRadius++
const weight = (1 - currentRadius / (radius + 1)) ** 2
rTotal += weight * imageData[pixelIndex * 4]
gTotal += weight * imageData[pixelIndex * 4 + 1]
bTotal += weight * imageData[pixelIndex * 4 + 2]
}
}
}
pixels[i * 4] = rTotal / totalWeight
pixels[i * 4 + 1] = gTotal / totalWeight
pixels[i * 4 + 2] = bTotal / totalWeight
}).setOutput([rowCount, columnCount])
const result = kernel(pixels.data, height, width, radius)
return new ImageData(result.flat(), width, height)
},
},
}

這里我們使用了GPU.js來實現(xiàn)了向四個方向的模糊濾鏡算法。在Vue框架中使用GPU計算非常的方便，只需要引入GPU.js并編寫合適的計算核心即可實現(xiàn)復雜計算。