mirror of
https://github.com/encounter/dawn-cmake.git
synced 2025-05-15 03:41:34 +00:00
deb4057d27
We now always use Tint. Bug: dawn:571 Change-Id: Ic65669a9e00493292ed60cde00af6fa3f6e55ec2 Reviewed-on: https://dawn-review.googlesource.com/c/dawn/+/65665 Commit-Queue: Corentin Wallez <cwallez@chromium.org> Reviewed-by: Ben Clayton <bclayton@google.com>
513 lines
22 KiB
C++
513 lines
22 KiB
C++
// Copyright 2021 The Dawn Authors
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include "tests/perf_tests/DawnPerfTest.h"
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#include "utils/WGPUHelpers.h"
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namespace {
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constexpr uint32_t kTileSize = 32u;
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const std::string& kMatMulFloatHeader = R"(
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[[block]] struct Uniforms {
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dimAOuter : u32;
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dimInner : u32;
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dimBOuter : u32;
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};
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[[block]] struct Matrix {
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numbers: array<f32>;
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};
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[[group(0), binding(0)]] var<storage, read> firstMatrix : Matrix;
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[[group(0), binding(1)]] var<storage, read> secondMatrix : Matrix;
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[[group(0), binding(2)]] var<storage, write> resultMatrix : Matrix;
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[[group(0), binding(3)]] var<uniform> uniforms : Uniforms;
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fn mm_readA(row : u32, col : u32) -> f32 {
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if (row < uniforms.dimAOuter && col < uniforms.dimInner)
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{
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let result : f32 = firstMatrix.numbers[row * uniforms.dimInner + col];
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return result;
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}
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return 0.;
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}
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fn mm_readB(row : u32, col : u32) -> f32 {
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if (row < uniforms.dimInner && col < uniforms.dimBOuter)
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{
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let result : f32 = secondMatrix.numbers[row * uniforms.dimBOuter + col];
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return result;
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}
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return 0.;
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}
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fn mm_write(row : u32, col : u32, value : f32) {
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if (row < uniforms.dimAOuter && col < uniforms.dimBOuter)
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{
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let index : u32 = col + row * uniforms.dimBOuter;
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resultMatrix.numbers[index] = value;
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}
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}
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let RowPerThread : u32 = 4u;
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let ColPerThread : u32 = 4u;
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let TileAOuter : u32 = 32u;
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let TileBOuter : u32 = 32u;
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let TileInner : u32 = 32u;)";
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const std::string& kMatMulFloatSharedArray1D = R"(
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var<workgroup> mm_Asub : array<f32, 1024>;
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var<workgroup> mm_Bsub : array<f32, 1024>;)";
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const std::string& kMatMulFloatSharedArray2D = R"(
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var<workgroup> mm_Asub : array<array<f32, 32>, 32>;
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var<workgroup> mm_Bsub : array<array<f32, 32>, 32>;)";
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const std::string& kMatMulFloatBodyPart1 = R"(
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[[stage(compute), workgroup_size(8, 8, 1)]]
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fn main([[builtin(local_invocation_id)]] local_id : vec3<u32>,
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[[builtin(global_invocation_id)]] global_id : vec3<u32>) {
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let tileRow : u32 = local_id.y * RowPerThread;
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let tileCol : u32 = local_id.x * ColPerThread;
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let globalRow : u32 = global_id.y * RowPerThread;
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let globalCol : u32 = global_id.x * ColPerThread;
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let numTiles : u32 = (uniforms.dimInner - 1u) / TileInner + 1u;
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var acc: array<f32, 16>;
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var ACached : f32;
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var BCached : array<f32, 4>;
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// Without this initialization strange values show up in acc.
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// TODO: Remove it once the following bug is fixed.
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// https://bugs.chromium.org/p/tint/issues/detail?id=759
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for (var index : u32 = 0u; index < RowPerThread * ColPerThread; index = index + 1u) {
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acc[index] = 0.;
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}
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let ColPerThreadA : u32 = TileInner / 8u;
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let tileColA : u32 = local_id.x * ColPerThreadA;
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let RowPerThreadB : u32 = TileInner / 8u;
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let tileRowB : u32 = local_id.y * RowPerThreadB;
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// Loop over shared dimension.
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for (var t : u32 = 0u; t < numTiles; t = t + 1u) {
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// Load one tile of A into local memory.
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for (var innerRow : u32 = 0u; innerRow < RowPerThread; innerRow = innerRow + 1u) {
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for (var innerCol : u32 = 0u; innerCol < ColPerThreadA; innerCol = innerCol + 1u) {
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let inputRow : u32 = tileRow + innerRow;
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let inputCol : u32 = tileColA + innerCol;)";
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const std::string& kMatMulFloatBodyPart2Array1D = R"(
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let index : u32 = inputRow * TileInner + inputCol;
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mm_Asub[index] = mm_readA(globalRow + innerRow, t * TileInner + inputCol);
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}
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}
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// Load one tile of B into local memory.
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for (var innerRow : u32 = 0u; innerRow < RowPerThreadB; innerRow = innerRow + 1u) {
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for (var innerCol : u32 = 0u; innerCol < ColPerThread; innerCol = innerCol + 1u) {
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let inputRow : u32 = tileRowB + innerRow;
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let inputCol : u32 = tileCol + innerCol;
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let index : u32 = inputRow * TileBOuter + inputCol;
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mm_Bsub[index] = mm_readB(t * TileInner + inputRow, globalCol + innerCol);;
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}
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}
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workgroupBarrier();
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// Compute acc values for a single thread.
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for (var k : u32 = 0u; k < TileInner; k = k + 1u) {
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for (var inner : u32 = 0u; inner < ColPerThread; inner = inner + 1u) {
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BCached[inner] = mm_Bsub[k * TileBOuter + tileCol + inner];
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}
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for (var innerRow : u32 = 0u; innerRow < RowPerThread; innerRow = innerRow + 1u) {
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ACached = mm_Asub[(tileRow + innerRow) * TileInner + k];)";
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const std::string& kMatMulFloatBodyPart2Array2D = R"(
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mm_Asub[inputRow][inputCol] = mm_readA(globalRow + innerRow, t * TileInner + inputCol);
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}
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}
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// Load one tile of B into local memory.
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for (var innerRow : u32 = 0u; innerRow < RowPerThreadB; innerRow = innerRow + 1u) {
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for (var innerCol : u32 = 0u; innerCol < ColPerThread; innerCol = innerCol + 1u) {
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let inputRow : u32 = tileRowB + innerRow;
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let inputCol : u32 = tileCol + innerCol;
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mm_Bsub[innerCol][inputCol] = mm_readB(t * TileInner + inputRow, globalCol + innerCol);;
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}
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}
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workgroupBarrier();
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// Compute acc values for a single thread.
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for (var k : u32 = 0u; k < TileInner; k = k + 1u) {
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for (var inner : u32 = 0u; inner < ColPerThread; inner = inner + 1u) {
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BCached[inner] = mm_Bsub[k][tileCol + inner];
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}
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for (var innerRow : u32 = 0u; innerRow < RowPerThread; innerRow = innerRow + 1u) {
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ACached = mm_Asub[tileRow + innerRow][k];)";
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const std::string& kMatMulFloatBodyPart3 = R"(
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for (var innerCol : u32 = 0u; innerCol < ColPerThread; innerCol = innerCol + 1u) {
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let index : u32 = innerRow * ColPerThread + innerCol;
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acc[index] = acc[index] + ACached * BCached[innerCol];
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}
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}
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}
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workgroupBarrier();
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}
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for (var innerRow : u32 = 0u; innerRow < RowPerThread; innerRow = innerRow + 1u) {
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for (var innerCol : u32 = 0u; innerCol < ColPerThread; innerCol = innerCol + 1u) {
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let index : u32 = innerRow * ColPerThread + innerCol;
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mm_write(globalRow + innerRow,
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globalCol + innerCol,
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acc[index]);
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}
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}
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})";
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const std::string& kMatMulFloatOneDimensionalSharedArray =
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kMatMulFloatHeader + kMatMulFloatSharedArray1D + kMatMulFloatBodyPart1 +
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kMatMulFloatBodyPart2Array1D + kMatMulFloatBodyPart3;
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const std::string& kMatMulFloatTwoDimensionalSharedArray =
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kMatMulFloatHeader + kMatMulFloatSharedArray2D + kMatMulFloatBodyPart1 +
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kMatMulFloatBodyPart2Array2D + kMatMulFloatBodyPart3;
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// The vec4 version requires that dimInner and dimBOuter are divisible by 4.
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const std::string& kMatMulVec4Header = R"(
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[[block]] struct Uniforms {
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dimAOuter : u32;
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dimInner : u32;
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dimBOuter : u32;
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};
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[[block]] struct Matrix {
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numbers: array<vec4<f32>>;
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};
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[[group(0), binding(0)]] var<storage, read> firstMatrix : Matrix;
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[[group(0), binding(1)]] var<storage, read> secondMatrix : Matrix;
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[[group(0), binding(2)]] var<storage, write> resultMatrix : Matrix;
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[[group(0), binding(3)]] var<uniform> uniforms : Uniforms;
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fn mm_readA(row : u32, col : u32) -> vec4<f32> {
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if (row < uniforms.dimAOuter && col < uniforms.dimInner)
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{
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let result : vec4<f32> = firstMatrix.numbers[row * uniforms.dimInner / 4u + col];
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return result;
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}
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return vec4<f32>(0.0, 0.0, 0.0, 0.0);
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}
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fn mm_readB(row : u32, col : u32) -> vec4<f32> {
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if (row < uniforms.dimInner && col < uniforms.dimBOuter)
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{
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let result : vec4<f32> = secondMatrix.numbers[row * uniforms.dimBOuter / 4u + col];
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return result;
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}
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return vec4<f32>(0.0, 0.0, 0.0, 0.0);
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}
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fn mm_write(row : u32, col : u32, value : vec4<f32>) {
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if (row < uniforms.dimAOuter && col < uniforms.dimBOuter)
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{
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let index : u32 = col + row * uniforms.dimBOuter / 4u;
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resultMatrix.numbers[index] = value;
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}
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}
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let RowPerThread : u32 = 4u;
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let ColPerThread : u32 = 4u;
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let TileOuter : u32 = 32u;
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let TileInner : u32 = 32u;)";
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const std::string& kMatMulVec4SharedArray1D = R"(
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var<workgroup> mm_Asub : array<vec4<f32>, 256>;
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var<workgroup> mm_Bsub : array<vec4<f32>, 256>;)";
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const std::string& kMatMulVec4SharedArray2D = R"(
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var<workgroup> mm_Asub : array<array<vec4<f32>, 8>, 32>;
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var<workgroup> mm_Bsub : array<array<vec4<f32>, 8>, 32>;)";
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const std::string& kMatMulVec4BodyPart1 = R"(
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[[stage(compute), workgroup_size(8, 8, 1)]]
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fn main([[builtin(local_invocation_id)]] local_id : vec3<u32>,
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[[builtin(global_invocation_id)]] global_id : vec3<u32>) {
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let tileRow : u32 = local_id.y * RowPerThread;
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let tileCol : u32 = local_id.x;
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let globalRow : u32 = global_id.y * RowPerThread;
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let globalCol : u32 = global_id.x;
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let numTiles : u32 = (uniforms.dimInner - 1u) / TileInner + 1u;
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var acc: array<vec4<f32>, 4>;
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var ACached : vec4<f32>;
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var BCached : array<vec4<f32>, 4>;
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// Without this initialization strange values show up in acc.
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// TODO: Remove it once the following bug is fixed.
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// https://bugs.chromium.org/p/tint/issues/detail?id=759
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for (var index : u32 = 0u; index < RowPerThread; index = index + 1u) {
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acc[index] = vec4<f32>(0.0, 0.0, 0.0, 0.0);
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}
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var globalColA : u32 = tileCol;
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let RowPerThreadB : u32 = TileInner / 8u;
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let tileRowB : u32 = local_id.y * RowPerThreadB;
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// Loop over shared dimension.
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for (var t : u32 = 0u; t < numTiles; t = t + 1u) {
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// Load one tile of A into local memory.
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for (var innerRow : u32 = 0u; innerRow < RowPerThread; innerRow = innerRow + 1u) {
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let inputRow : u32 = tileRow + innerRow;
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let inputCol : u32 = tileCol;)";
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const std::string& kMatMulVec4BodyPart2Array1D = R"(
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let index : u32 = inputRow * TileInner / ColPerThread + inputCol;
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mm_Asub[index] = mm_readA(globalRow + innerRow, globalColA);
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}
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globalColA = globalColA + TileInner / ColPerThread;
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// Load one tile of B into local memory.
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for (var innerRow : u32 = 0u; innerRow < RowPerThreadB; innerRow = innerRow + 1u) {
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let inputRow : u32 = tileRowB + innerRow;
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let inputCol : u32 = tileCol;
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let index : u32 = inputRow * TileOuter / ColPerThread + inputCol;
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mm_Bsub[index] = mm_readB(t * TileInner + inputRow, globalCol);;
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}
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workgroupBarrier();
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// Compute acc values for a single thread.
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for (var k : u32 = 0u; k < TileInner / ColPerThread; k = k + 1u) {
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BCached[0] = mm_Bsub[(k * ColPerThread) * (TileOuter / ColPerThread) + tileCol];
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BCached[1] = mm_Bsub[(k * ColPerThread + 1u) * (TileOuter / ColPerThread) + tileCol];
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BCached[2] = mm_Bsub[(k * ColPerThread + 2u) * (TileOuter / ColPerThread) + tileCol];
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BCached[3] = mm_Bsub[(k * ColPerThread + 3u) * (TileOuter / ColPerThread) + tileCol];
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for (var i : u32 = 0u; i < RowPerThread; i = i + 1u) {
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ACached = mm_Asub[(tileRow + i) * (TileInner / ColPerThread) + k];)";
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const std::string& kMatMulVec4BodyPart2Array2D = R"(
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mm_Asub[inputRow][inputCol] = mm_readA(globalRow + innerRow, globalColA);
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}
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globalColA = globalColA + TileInner / ColPerThread;
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// Load one tile of B into local memory.
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for (var innerRow : u32 = 0u; innerRow < RowPerThreadB; innerRow = innerRow + 1u) {
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let inputRow : u32 = tileRowB + innerRow;
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let inputCol : u32 = tileCol;
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mm_Bsub[inputRow][inputCol] = mm_readB(t * TileInner + inputRow, globalCol);;
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}
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workgroupBarrier();
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// Compute acc values for a single thread.
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for (var k : u32 = 0u; k < TileInner / ColPerThread; k = k + 1u) {
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BCached[0] = mm_Bsub[k * ColPerThread][tileCol];
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BCached[1] = mm_Bsub[k * ColPerThread + 1u][tileCol];
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BCached[2] = mm_Bsub[k * ColPerThread + 2u][tileCol];
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BCached[3] = mm_Bsub[k * ColPerThread + 3u][tileCol];
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for (var i : u32 = 0u; i < RowPerThread; i = i + 1u) {
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ACached = mm_Asub[tileRow + i][k];)";
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const std::string& kMatMulVec4BodyPart3 = R"(
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acc[i] = BCached[0] * ACached.x + acc[i];
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acc[i] = BCached[1] * ACached.y + acc[i];
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acc[i] = BCached[2] * ACached.z + acc[i];
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acc[i] = BCached[3] * ACached.w + acc[i];
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}
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}
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workgroupBarrier();
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}
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for (var innerRow : u32 = 0u; innerRow < RowPerThread; innerRow = innerRow + 1u) {
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mm_write(globalRow + innerRow,
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globalCol,
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acc[innerRow]);
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}
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})";
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const std::string& kMatMulVec4OneDimensionalSharedArray =
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kMatMulVec4Header + kMatMulVec4SharedArray1D + kMatMulVec4BodyPart1 +
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kMatMulVec4BodyPart2Array1D + kMatMulVec4BodyPart3;
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const std::string& kMatMulVec4TwoDimensionalSharedArray =
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kMatMulVec4Header + kMatMulVec4SharedArray2D + kMatMulVec4BodyPart1 +
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kMatMulVec4BodyPart2Array2D + kMatMulVec4BodyPart3;
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constexpr unsigned int kNumIterations = 50;
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enum class MatMulMethod {
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MatMulFloatOneDimSharedArray,
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MatMulFloatTwoDimSharedArray,
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MatMulVec4OneDimSharedArray,
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MatMulVec4TwoDimSharedArray
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};
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std::ostream& operator<<(std::ostream& ostream, const MatMulMethod& matMulMethod) {
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switch (matMulMethod) {
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case MatMulMethod::MatMulFloatOneDimSharedArray:
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ostream << "MatMulFloatOneDimSharedArray";
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break;
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case MatMulMethod::MatMulFloatTwoDimSharedArray:
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ostream << "MatMulFloatTwoDimSharedArray";
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break;
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case MatMulMethod::MatMulVec4OneDimSharedArray:
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ostream << "MatMulVec4OneDimSharedArray";
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break;
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case MatMulMethod::MatMulVec4TwoDimSharedArray:
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ostream << "MatMulVec4TwoDimSharedArray";
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break;
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}
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return ostream;
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}
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using DimAOuter = uint32_t;
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using DimInner = uint32_t;
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using DimBOuter = uint32_t;
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DAWN_TEST_PARAM_STRUCT(ShaderRobustnessParams, MatMulMethod, DimAOuter, DimInner, DimBOuter)
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} // namespace
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// Test the execution time of matrix multiplication (A [dimAOuter, dimInner] * B [dimInner,
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// dimBOuter]) on the GPU and see the difference between robustness on and off.
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class ShaderRobustnessPerf : public DawnPerfTestWithParams<ShaderRobustnessParams> {
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public:
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ShaderRobustnessPerf()
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: DawnPerfTestWithParams(kNumIterations, 1),
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mDimAOuter(GetParam().mDimAOuter),
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mDimInner(GetParam().mDimInner),
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mDimBOuter(GetParam().mDimBOuter) {
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}
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~ShaderRobustnessPerf() override = default;
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void SetUp() override;
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private:
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void Step() override;
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wgpu::BindGroup mBindGroup;
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wgpu::ComputePipeline mPipeline;
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uint32_t mDimAOuter;
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uint32_t mDimInner;
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uint32_t mDimBOuter;
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};
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void ShaderRobustnessPerf::SetUp() {
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DawnPerfTestWithParams<ShaderRobustnessParams>::SetUp();
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// TODO(crbug.com/dawn/786): D3D12_Microsoft_Basic_Render_Driver_CPU
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DAWN_SUPPRESS_TEST_IF(IsD3D12() && IsWARP());
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// TODO(crbug.com/dawn/945): Generation via SPIRV-Cross fails
|
|
DAWN_SUPPRESS_TEST_IF(IsOpenGL());
|
|
|
|
const size_t dataASize = mDimAOuter * mDimInner;
|
|
std::vector<float> dataA(dataASize);
|
|
uint64_t byteASize = sizeof(float) * dataA.size();
|
|
// It's ok to use all zeros to do the matrix multiplication for performance test.
|
|
wgpu::Buffer bufA =
|
|
utils::CreateBufferFromData(device, dataA.data(), byteASize, wgpu::BufferUsage::Storage);
|
|
|
|
const size_t dataBSize = mDimInner * mDimBOuter;
|
|
std::vector<float> dataB(dataBSize);
|
|
uint64_t byteBSize = sizeof(float) * dataB.size();
|
|
wgpu::Buffer bufB =
|
|
utils::CreateBufferFromData(device, dataB.data(), byteBSize, wgpu::BufferUsage::Storage);
|
|
|
|
uint64_t byteDstSize = sizeof(float) * mDimAOuter * mDimBOuter;
|
|
wgpu::BufferDescriptor desc = {};
|
|
desc.usage = wgpu::BufferUsage::Storage;
|
|
desc.size = byteDstSize;
|
|
wgpu::Buffer dst = device.CreateBuffer(&desc);
|
|
|
|
uint32_t uniformData[] = {mDimAOuter, mDimInner, mDimBOuter};
|
|
wgpu::Buffer uniformBuffer = utils::CreateBufferFromData(
|
|
device, uniformData, sizeof(uniformData), wgpu::BufferUsage::Uniform);
|
|
|
|
wgpu::ShaderModule module;
|
|
switch (GetParam().mMatMulMethod) {
|
|
case MatMulMethod::MatMulFloatOneDimSharedArray: {
|
|
module =
|
|
utils::CreateShaderModule(device, kMatMulFloatOneDimensionalSharedArray.c_str());
|
|
break;
|
|
}
|
|
|
|
case MatMulMethod::MatMulFloatTwoDimSharedArray: {
|
|
module =
|
|
utils::CreateShaderModule(device, kMatMulFloatTwoDimensionalSharedArray.c_str());
|
|
break;
|
|
}
|
|
|
|
case MatMulMethod::MatMulVec4OneDimSharedArray: {
|
|
module =
|
|
utils::CreateShaderModule(device, kMatMulVec4OneDimensionalSharedArray.c_str());
|
|
break;
|
|
}
|
|
|
|
case MatMulMethod::MatMulVec4TwoDimSharedArray: {
|
|
module =
|
|
utils::CreateShaderModule(device, kMatMulVec4TwoDimensionalSharedArray.c_str());
|
|
break;
|
|
}
|
|
}
|
|
|
|
wgpu::ComputePipelineDescriptor csDesc;
|
|
csDesc.compute.module = module;
|
|
csDesc.compute.entryPoint = "main";
|
|
mPipeline = device.CreateComputePipeline(&csDesc);
|
|
|
|
mBindGroup = utils::MakeBindGroup(device, mPipeline.GetBindGroupLayout(0),
|
|
{
|
|
{0, bufA, 0, byteASize},
|
|
{1, bufB, 0, byteBSize},
|
|
{2, dst, 0, byteDstSize},
|
|
{3, uniformBuffer, 0, sizeof(uniformData)},
|
|
});
|
|
}
|
|
|
|
void ShaderRobustnessPerf::Step() {
|
|
wgpu::CommandBuffer commands;
|
|
{
|
|
wgpu::CommandEncoder encoder = device.CreateCommandEncoder();
|
|
wgpu::ComputePassEncoder pass = encoder.BeginComputePass();
|
|
pass.SetPipeline(mPipeline);
|
|
pass.SetBindGroup(0, mBindGroup);
|
|
for (unsigned int i = 0; i < kNumIterations; ++i) {
|
|
pass.Dispatch(ceil(float(mDimBOuter) / float(kTileSize)),
|
|
ceil(float(mDimAOuter) / float(kTileSize)), 1);
|
|
}
|
|
pass.EndPass();
|
|
|
|
commands = encoder.Finish();
|
|
}
|
|
|
|
queue.Submit(1, &commands);
|
|
}
|
|
|
|
TEST_P(ShaderRobustnessPerf, Run) {
|
|
RunTest();
|
|
}
|
|
|
|
DAWN_INSTANTIATE_TEST_P(ShaderRobustnessPerf,
|
|
{D3D12Backend(), D3D12Backend({"disable_robustness"}, {}), MetalBackend(),
|
|
MetalBackend({"disable_robustness"}, {}), OpenGLBackend(),
|
|
OpenGLBackend({"disable_robustness"}, {}), VulkanBackend(),
|
|
VulkanBackend({"disable_robustness"}, {})},
|
|
{MatMulMethod::MatMulFloatOneDimSharedArray,
|
|
MatMulMethod::MatMulFloatTwoDimSharedArray,
|
|
MatMulMethod::MatMulVec4OneDimSharedArray,
|
|
MatMulMethod::MatMulVec4TwoDimSharedArray},
|
|
{512u},
|
|
{512u},
|
|
{512u});
|