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webgpu: Reduce binary ops shader variants #5791

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4 changes: 2 additions & 2 deletions tfjs-backend-webgpu/src/kernels/Prelu.ts
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Original file line number Diff line number Diff line change
Expand Up @@ -20,14 +20,14 @@ import {KernelConfig, KernelFunc, Prelu, PreluInputs, TensorInfo} from '@tensorf
import {WebGPUBackend} from '../backend_webgpu';

import {BinaryOpType} from './binary_op_util';
import {BinaryOpProgram} from './binary_op_webgpu';
import {getBinaryProgram} from './binary_ops';

export function prelu(args: {inputs: PreluInputs, backend: WebGPUBackend}):
TensorInfo {
const {inputs, backend} = args;
const {x, alpha} = inputs;

const program = new BinaryOpProgram(BinaryOpType.PRELU, x.shape, alpha.shape);
const program = getBinaryProgram(BinaryOpType.PRELU, x.shape, alpha.shape);
return backend.runWebGPUProgram(program, [x, alpha], 'float32');
}

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47 changes: 18 additions & 29 deletions tfjs-backend-webgpu/src/kernels/binary_op_shared_webgpu.ts
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Expand Up @@ -15,8 +15,6 @@
* =============================================================================
*/

import {backend_util} from '@tensorflow/tfjs-core';

import {getMainHeaderAndGlobalIndexString} from '../shader_preprocessor';
import {computeDispatch, flatDispatchLayout} from '../webgpu_util';
import {BinaryOpType, getBinaryOpString} from './binary_op_util';
Expand All @@ -29,66 +27,57 @@ export class BinaryOpSharedProgram implements WebGPUProgram {
dispatchLayout: {x: number[]};
dispatch: [number, number, number];
variableNames = ['A', 'B'];
workPerThread: number;
workPerThread = 4;
workGroupSize: [number, number, number];
useSharedMemoryWithB: boolean;
lastDimensionSize: number;
isScater: boolean;
op: BinaryOpType;
size = true;

constructor(
op: BinaryOpType, aShape: number[], bShape: number[],
useSharedMemoryWithB: boolean) {
op: BinaryOpType, outputShape: number[], useSharedMemoryWithB: boolean,
isScater: boolean) {
// This is an experimental value when using shared memory.
// Note that the maximum of workgroup X dimension is 256.
const workGroupSizeX = 256;
this.workGroupSize = [workGroupSizeX, 1, 1];
this.outputShape = backend_util.assertAndGetBroadcastShape(aShape, bShape);
this.outputShape = outputShape;
this.dispatchLayout = flatDispatchLayout(this.outputShape);
this.lastDimensionSize = useSharedMemoryWithB ? bShape[0] : aShape[0];
if (this.lastDimensionSize < 256) {
this.workPerThread = 1;
} else if (this.lastDimensionSize < 512) {
this.workPerThread = 2;
} else {
this.workPerThread = 4;
}
this.isScater = isScater;
this.dispatch = computeDispatch(
this.dispatchLayout, this.outputShape, this.workGroupSize,
[this.workPerThread, 1, 1]);

this.useSharedMemoryWithB = useSharedMemoryWithB;
this.op = op;
// this.lastDimensionSize is used as sharedBuf array size, so can not be
// used as uniform.
this.shaderKey = `binaryShared_${op}_${this.lastDimensionSize}_${
this.useSharedMemoryWithB}`;
this.shaderKey =
`binaryShared_${op}_${this.useSharedMemoryWithB}_${isScater}`;
}

getUserCode(): string {
const sharedIndexSnippet = this.lastDimensionSize > 1 ?
`coords[${this.outputShape.length - 1}]` :
'0';
const sharedIndexSnippet =
this.isScater ? '0' : `coords[${this.outputShape.length - 1}]`;
const accessDataSnippet = this.useSharedMemoryWithB ?
`let a = getAAtOutCoordsByCoords(coords);
`let a = getAAtOutCoordsByGlobalIndex(flatIndex);
let b = sharedBuf[${sharedIndexSnippet}];` :
`let a = sharedBuf[${sharedIndexSnippet}];
let b = getBAtOutCoordsByCoords(coords);`;
let b = getBAtOutCoordsByGlobalIndex(flatIndex);`;

const opStr = getBinaryOpString(this.op, false);
const userCode = `
fn binaryOperation(a : f32, b : f32) -> f32 {
${opStr}
${getBinaryOpString(this.op, false)}
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LGTM. Do you have warmup and perf data?
nit, false can be removed.

}
var<workgroup> sharedBuf : array<f32, ${this.lastDimensionSize}>;

var<workgroup> sharedBuf : array<f32, ${
this.workGroupSize[0] * this.workPerThread}>;
${getMainHeaderAndGlobalIndexString()}

// Fill in the shared memory buffer. Here we need a loop to make sure
// that all data in A|B are uploaded when |sharedMemorySize| is larger
// than work group size.
for(var localIndex = i32(localId.x); localIndex < ${
this.lastDimensionSize}; localIndex = localIndex + ${
this.workGroupSize[0]}) {
this.useSharedMemoryWithB ? 'uniforms.bShape' : 'uniforms.aShape'};
localIndex = localIndex + ${this.workGroupSize[0]}) {
sharedBuf[localIndex] = f32(${
this.useSharedMemoryWithB ? 'B' : 'A'}.numbers[localIndex]);
}
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6 changes: 2 additions & 4 deletions tfjs-backend-webgpu/src/kernels/binary_op_vec4_webgpu.ts
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Expand Up @@ -15,7 +15,6 @@
* =============================================================================
*/

import {backend_util} from '@tensorflow/tfjs-core';
import {getMainHeaderAndGlobalIndexString} from '../shader_preprocessor';
import {computeDispatch, flatDispatchLayout} from '../webgpu_util';
import {BinaryOpType, getBinaryOpString} from './binary_op_util';
Expand All @@ -33,13 +32,12 @@ export class BinaryOpVec4Program implements WebGPUProgram {
isVec4 = true;
op: BinaryOpType;
size = true;
fitShape: boolean;

constructor(op: BinaryOpType, aShape: number[], bShape: number[]) {
constructor(op: BinaryOpType, outputShape: number[]) {
// TODO(jiajia.qin@intel.com): Heuristically select a good work group size.
const workGroupSizeX = 128;
this.workGroupSize = [workGroupSizeX, 1, 1];
this.outputShape = backend_util.assertAndGetBroadcastShape(aShape, bShape);
this.outputShape = outputShape;
this.dispatchLayout = flatDispatchLayout(this.outputShape);
this.dispatch = computeDispatch(
this.dispatchLayout, this.outputShape, this.workGroupSize,
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5 changes: 2 additions & 3 deletions tfjs-backend-webgpu/src/kernels/binary_op_webgpu.ts
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Expand Up @@ -15,7 +15,6 @@
* =============================================================================
*/

import {backend_util} from '@tensorflow/tfjs-core';
import {getMainHeaderAndGlobalIndexString} from '../shader_preprocessor';
import {computeDispatch, flatDispatchLayout} from '../webgpu_util';
import {BinaryOpType, getBinaryOpString} from './binary_op_util';
Expand All @@ -32,11 +31,11 @@ export class BinaryOpProgram implements WebGPUProgram {
op: BinaryOpType;
size = true;

constructor(op: BinaryOpType, aShape: number[], bShape: number[]) {
constructor(op: BinaryOpType, outputShape: number[]) {
// TODO(jiajia.qin@intel.com): Heuristically select a good work group size.
const workGroupSizeX = 128;
this.workGroupSize = [workGroupSizeX, 1, 1];
this.outputShape = backend_util.assertAndGetBroadcastShape(aShape, bShape);
this.outputShape = outputShape;
this.dispatchLayout = flatDispatchLayout(this.outputShape);

this.dispatch = computeDispatch(
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18 changes: 11 additions & 7 deletions tfjs-backend-webgpu/src/kernels/binary_ops.ts
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Original file line number Diff line number Diff line change
Expand Up @@ -15,26 +15,30 @@
* =============================================================================
*/

import {util} from '@tensorflow/tfjs-core';
import {backend_util, util} from '@tensorflow/tfjs-core';

import {BinaryOpSharedProgram} from './binary_op_shared_webgpu';
import {BinaryOpType} from './binary_op_util';
import {BinaryOpVec4Program} from './binary_op_vec4_webgpu';
import {BinaryOpProgram} from './binary_op_webgpu';
import {BinaryOpType} from './binary_op_util';

export function getBinaryProgram(
op: BinaryOpType, aShape: number[], bShape: number[]) {
const outputShape = backend_util.assertAndGetBroadcastShape(aShape, bShape);
const useVec4 =
util.arraysEqual(aShape, bShape) && util.sizeFromShape(aShape) % 4 === 0;
if (useVec4) {
return new BinaryOpVec4Program(op, aShape, bShape);
return new BinaryOpVec4Program(op, outputShape);
}
const useSharedMemoryWithA =
aShape.length === 1 && bShape.length > 1 && aShape[0] < 1024;
aShape.length === 1 && bShape.length > 1 && aShape[0] < 512;
const useSharedMemoryWithB =
bShape.length === 1 && aShape.length > 1 && bShape[0] < 1024;
bShape.length === 1 && aShape.length > 1 && bShape[0] < 512;
if (useSharedMemoryWithA || useSharedMemoryWithB) {
return new BinaryOpSharedProgram(op, aShape, bShape, useSharedMemoryWithB);
const isScater = useSharedMemoryWithB ? bShape[0] === 1 : aShape[0] === 1;
return new BinaryOpSharedProgram(
op, outputShape, useSharedMemoryWithB, isScater);
} else {
return new BinaryOpProgram(op, aShape, bShape);
return new BinaryOpProgram(op, outputShape);
}
}