| // Copyright 2021 The Dawn & Tint Authors |
| // |
| // Redistribution and use in source and binary forms, with or without |
| // modification, are permitted provided that the following conditions are met: |
| // |
| // 1. Redistributions of source code must retain the above copyright notice, this |
| // list of conditions and the following disclaimer. |
| // |
| // 2. Redistributions in binary form must reproduce the above copyright notice, |
| // this list of conditions and the following disclaimer in the documentation |
| // and/or other materials provided with the distribution. |
| // |
| // 3. Neither the name of the copyright holder nor the names of its |
| // contributors may be used to endorse or promote products derived from |
| // this software without specific prior written permission. |
| // |
| // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" |
| // AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE |
| // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE |
| // DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE |
| // FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL |
| // DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR |
| // SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER |
| // CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, |
| // OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE |
| // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. |
| |
| #include <string> |
| #include <vector> |
| |
| #include "dawn/tests/perf_tests/DawnPerfTest.h" |
| #include "dawn/utils/WGPUHelpers.h" |
| |
| namespace dawn { |
| namespace { |
| |
| constexpr uint32_t kTileSize = 32u; |
| |
| const std::string& kMatMulFloatHeader = R"( |
| struct Uniforms { |
| dimAOuter : u32, |
| dimInner : u32, |
| dimBOuter : u32, |
| } |
| struct Matrix { |
| numbers: array<f32> |
| } |
| |
| @group(0) @binding(0) var<storage, read> firstMatrix : Matrix; |
| @group(0) @binding(1) var<storage, read> secondMatrix : Matrix; |
| @group(0) @binding(2) var<storage, read_write> resultMatrix : Matrix; |
| @group(0) @binding(3) var<uniform> uniforms : Uniforms; |
| |
| fn mm_readA(row : u32, col : u32) -> f32 { |
| if (row < uniforms.dimAOuter && col < uniforms.dimInner) |
| { |
| let result : f32 = firstMatrix.numbers[row * uniforms.dimInner + col]; |
| return result; |
| } |
| return 0.; |
| } |
| |
| fn mm_readB(row : u32, col : u32) -> f32 { |
| if (row < uniforms.dimInner && col < uniforms.dimBOuter) |
| { |
| let result : f32 = secondMatrix.numbers[row * uniforms.dimBOuter + col]; |
| return result; |
| } |
| return 0.; |
| } |
| |
| fn mm_write(row : u32, col : u32, value : f32) { |
| if (row < uniforms.dimAOuter && col < uniforms.dimBOuter) |
| { |
| let index : u32 = col + row * uniforms.dimBOuter; |
| resultMatrix.numbers[index] = value; |
| } |
| } |
| |
| const RowPerThread : u32 = 4u; |
| const ColPerThread : u32 = 4u; |
| const TileAOuter : u32 = 32u; |
| const TileBOuter : u32 = 32u; |
| const TileInner : u32 = 32u;)"; |
| |
| const std::string& kMatMulFloatSharedArray1D = R"( |
| var<workgroup> mm_Asub : array<f32, 1024>; |
| var<workgroup> mm_Bsub : array<f32, 1024>;)"; |
| const std::string& kMatMulFloatSharedArray2D = R"( |
| var<workgroup> mm_Asub : array<array<f32, 32>, 32>; |
| var<workgroup> mm_Bsub : array<array<f32, 32>, 32>;)"; |
| const std::string& kMatMulFloatBodyPart1 = R"( |
| @compute @workgroup_size(8, 8, 1) |
| fn main(@builtin(local_invocation_id) local_id : vec3u, |
| @builtin(global_invocation_id) global_id : vec3u) { |
| let tileRow : u32 = local_id.y * RowPerThread; |
| let tileCol : u32 = local_id.x * ColPerThread; |
| |
| let globalRow : u32 = global_id.y * RowPerThread; |
| let globalCol : u32 = global_id.x * ColPerThread; |
| |
| let numTiles : u32 = (uniforms.dimInner - 1u) / TileInner + 1u; |
| |
| var acc: array<f32, 16>; |
| var ACached : f32; |
| var BCached : array<f32, 4>; |
| |
| let ColPerThreadA : u32 = TileInner / 8u; |
| let tileColA : u32 = local_id.x * ColPerThreadA; |
| let RowPerThreadB : u32 = TileInner / 8u; |
| let tileRowB : u32 = local_id.y * RowPerThreadB; |
| |
| // Loop over shared dimension. |
| for (var t : u32 = 0u; t < numTiles; t = t + 1u) { |
| // Load one tile of A into local memory. |
| for (var innerRow : u32 = 0u; innerRow < RowPerThread; innerRow = innerRow + 1u) { |
| for (var innerCol : u32 = 0u; innerCol < ColPerThreadA; innerCol = innerCol + 1u) { |
| let inputRow : u32 = tileRow + innerRow; |
| let inputCol : u32 = tileColA + innerCol;)"; |
| const std::string& kMatMulFloatBodyPart2Array1D = R"( |
| let index : u32 = inputRow * TileInner + inputCol; |
| mm_Asub[index] = mm_readA(globalRow + innerRow, t * TileInner + inputCol); |
| } |
| } |
| // Load one tile of B into local memory. |
| for (var innerRow : u32 = 0u; innerRow < RowPerThreadB; innerRow = innerRow + 1u) { |
| for (var innerCol : u32 = 0u; innerCol < ColPerThread; innerCol = innerCol + 1u) { |
| let inputRow : u32 = tileRowB + innerRow; |
| let inputCol : u32 = tileCol + innerCol; |
| let index : u32 = inputRow * TileBOuter + inputCol; |
| |
| mm_Bsub[index] = mm_readB(t * TileInner + inputRow, globalCol + innerCol);; |
| } |
| } |
| |
| workgroupBarrier(); |
| |
| // Compute acc values for a single thread. |
| for (var k : u32 = 0u; k < TileInner; k = k + 1u) { |
| for (var inner : u32 = 0u; inner < ColPerThread; inner = inner + 1u) { |
| BCached[inner] = mm_Bsub[k * TileBOuter + tileCol + inner]; |
| } |
| |
| for (var innerRow : u32 = 0u; innerRow < RowPerThread; innerRow = innerRow + 1u) { |
| ACached = mm_Asub[(tileRow + innerRow) * TileInner + k];)"; |
| const std::string& kMatMulFloatBodyPart2Array2D = R"( |
| mm_Asub[inputRow][inputCol] = mm_readA(globalRow + innerRow, t * TileInner + inputCol); |
| } |
| } |
| // Load one tile of B into local memory. |
| for (var innerRow : u32 = 0u; innerRow < RowPerThreadB; innerRow = innerRow + 1u) { |
| for (var innerCol : u32 = 0u; innerCol < ColPerThread; innerCol = innerCol + 1u) { |
| let inputRow : u32 = tileRowB + innerRow; |
| let inputCol : u32 = tileCol + innerCol; |
| |
| mm_Bsub[innerCol][inputCol] = mm_readB(t * TileInner + inputRow, globalCol + innerCol);; |
| } |
| } |
| |
| workgroupBarrier(); |
| |
| // Compute acc values for a single thread. |
| for (var k : u32 = 0u; k < TileInner; k = k + 1u) { |
| for (var inner : u32 = 0u; inner < ColPerThread; inner = inner + 1u) { |
| BCached[inner] = mm_Bsub[k][tileCol + inner]; |
| } |
| |
| for (var innerRow : u32 = 0u; innerRow < RowPerThread; innerRow = innerRow + 1u) { |
| ACached = mm_Asub[tileRow + innerRow][k];)"; |
| const std::string& kMatMulFloatBodyPart3 = R"( |
| for (var innerCol : u32 = 0u; innerCol < ColPerThread; innerCol = innerCol + 1u) { |
| let index : u32 = innerRow * ColPerThread + innerCol; |
| acc[index] = acc[index] + ACached * BCached[innerCol]; |
| } |
| } |
| } |
| |
| workgroupBarrier(); |
| } |
| |
| for (var innerRow : u32 = 0u; innerRow < RowPerThread; innerRow = innerRow + 1u) { |
| for (var innerCol : u32 = 0u; innerCol < ColPerThread; innerCol = innerCol + 1u) { |
| let index : u32 = innerRow * ColPerThread + innerCol; |
| mm_write(globalRow + innerRow, |
| globalCol + innerCol, |
| acc[index]); |
| } |
| } |
| })"; |
| const std::string& kMatMulFloatOneDimensionalSharedArray = |
| kMatMulFloatHeader + kMatMulFloatSharedArray1D + kMatMulFloatBodyPart1 + |
| kMatMulFloatBodyPart2Array1D + kMatMulFloatBodyPart3; |
| |
| const std::string& kMatMulFloatTwoDimensionalSharedArray = |
| kMatMulFloatHeader + kMatMulFloatSharedArray2D + kMatMulFloatBodyPart1 + |
| kMatMulFloatBodyPart2Array2D + kMatMulFloatBodyPart3; |
| |
| // The vec4 version requires that dimInner and dimBOuter are divisible by 4. |
| const std::string& kMatMulVec4Header = R"( |
| struct Uniforms { |
| dimAOuter : u32, |
| dimInner : u32, |
| dimBOuter : u32, |
| } |
| struct Matrix { |
| numbers: array<vec4f> |
| } |
| |
| @group(0) @binding(0) var<storage, read> firstMatrix : Matrix; |
| @group(0) @binding(1) var<storage, read> secondMatrix : Matrix; |
| @group(0) @binding(2) var<storage, read_write> resultMatrix : Matrix; |
| @group(0) @binding(3) var<uniform> uniforms : Uniforms; |
| |
| fn mm_readA(row : u32, col : u32) -> vec4f { |
| if (row < uniforms.dimAOuter && col < uniforms.dimInner) |
| { |
| let result : vec4f = firstMatrix.numbers[row * uniforms.dimInner / 4u + col]; |
| return result; |
| } |
| return vec4f(0.0, 0.0, 0.0, 0.0); |
| } |
| |
| fn mm_readB(row : u32, col : u32) -> vec4f { |
| if (row < uniforms.dimInner && col < uniforms.dimBOuter) |
| { |
| let result : vec4f = secondMatrix.numbers[row * uniforms.dimBOuter / 4u + col]; |
| return result; |
| } |
| return vec4f(0.0, 0.0, 0.0, 0.0); |
| } |
| |
| fn mm_write(row : u32, col : u32, value : vec4f) { |
| if (row < uniforms.dimAOuter && col < uniforms.dimBOuter) |
| { |
| let index : u32 = col + row * uniforms.dimBOuter / 4u; |
| resultMatrix.numbers[index] = value; |
| } |
| } |
| |
| const RowPerThread : u32 = 4u; |
| const ColPerThread : u32 = 4u; |
| const TileOuter : u32 = 32u; |
| const TileInner : u32 = 32u;)"; |
| const std::string& kMatMulVec4SharedArray1D = R"( |
| var<workgroup> mm_Asub : array<vec4f, 256>; |
| var<workgroup> mm_Bsub : array<vec4f, 256>;)"; |
| const std::string& kMatMulVec4SharedArray2D = R"( |
| var<workgroup> mm_Asub : array<array<vec4f, 8>, 32>; |
| var<workgroup> mm_Bsub : array<array<vec4f, 8>, 32>;)"; |
| const std::string& kMatMulVec4BodyPart1 = R"( |
| @compute @workgroup_size(8, 8, 1) |
| fn main(@builtin(local_invocation_id) local_id : vec3u, |
| @builtin(global_invocation_id) global_id : vec3u) { |
| let tileRow : u32 = local_id.y * RowPerThread; |
| let tileCol : u32 = local_id.x; |
| |
| let globalRow : u32 = global_id.y * RowPerThread; |
| let globalCol : u32 = global_id.x; |
| |
| let numTiles : u32 = (uniforms.dimInner - 1u) / TileInner + 1u; |
| |
| var acc: array<vec4f, 4>; |
| var ACached : vec4f; |
| var BCached : array<vec4f, 4>; |
| |
| var globalColA : u32 = tileCol; |
| let RowPerThreadB : u32 = TileInner / 8u; |
| let tileRowB : u32 = local_id.y * RowPerThreadB; |
| |
| // Loop over shared dimension. |
| for (var t : u32 = 0u; t < numTiles; t = t + 1u) { |
| // Load one tile of A into local memory. |
| for (var innerRow : u32 = 0u; innerRow < RowPerThread; innerRow = innerRow + 1u) { |
| let inputRow : u32 = tileRow + innerRow; |
| let inputCol : u32 = tileCol;)"; |
| const std::string& kMatMulVec4BodyPart2Array1D = R"( |
| let index : u32 = inputRow * TileInner / ColPerThread + inputCol; |
| mm_Asub[index] = mm_readA(globalRow + innerRow, globalColA); |
| } |
| globalColA = globalColA + TileInner / ColPerThread; |
| |
| // Load one tile of B into local memory. |
| for (var innerRow : u32 = 0u; innerRow < RowPerThreadB; innerRow = innerRow + 1u) { |
| let inputRow : u32 = tileRowB + innerRow; |
| let inputCol : u32 = tileCol; |
| let index : u32 = inputRow * TileOuter / ColPerThread + inputCol; |
| mm_Bsub[index] = mm_readB(t * TileInner + inputRow, globalCol);; |
| } |
| |
| workgroupBarrier(); |
| |
| // Compute acc values for a single thread. |
| for (var k : u32 = 0u; k < TileInner / ColPerThread; k = k + 1u) { |
| BCached[0] = mm_Bsub[(k * ColPerThread) * (TileOuter / ColPerThread) + tileCol]; |
| BCached[1] = mm_Bsub[(k * ColPerThread + 1u) * (TileOuter / ColPerThread) + tileCol]; |
| BCached[2] = mm_Bsub[(k * ColPerThread + 2u) * (TileOuter / ColPerThread) + tileCol]; |
| BCached[3] = mm_Bsub[(k * ColPerThread + 3u) * (TileOuter / ColPerThread) + tileCol]; |
| |
| for (var i : u32 = 0u; i < RowPerThread; i = i + 1u) { |
| ACached = mm_Asub[(tileRow + i) * (TileInner / ColPerThread) + k];)"; |
| const std::string& kMatMulVec4BodyPart2Array2D = R"( |
| mm_Asub[inputRow][inputCol] = mm_readA(globalRow + innerRow, globalColA); |
| } |
| globalColA = globalColA + TileInner / ColPerThread; |
| |
| // Load one tile of B into local memory. |
| for (var innerRow : u32 = 0u; innerRow < RowPerThreadB; innerRow = innerRow + 1u) { |
| let inputRow : u32 = tileRowB + innerRow; |
| let inputCol : u32 = tileCol; |
| mm_Bsub[inputRow][inputCol] = mm_readB(t * TileInner + inputRow, globalCol);; |
| } |
| |
| workgroupBarrier(); |
| |
| // Compute acc values for a single thread. |
| for (var k : u32 = 0u; k < TileInner / ColPerThread; k = k + 1u) { |
| BCached[0] = mm_Bsub[k * ColPerThread][tileCol]; |
| BCached[1] = mm_Bsub[k * ColPerThread + 1u][tileCol]; |
| BCached[2] = mm_Bsub[k * ColPerThread + 2u][tileCol]; |
| BCached[3] = mm_Bsub[k * ColPerThread + 3u][tileCol]; |
| |
| for (var i : u32 = 0u; i < RowPerThread; i = i + 1u) { |
| ACached = mm_Asub[tileRow + i][k];)"; |
| const std::string& kMatMulVec4BodyPart3 = R"( |
| acc[i] = BCached[0] * ACached.x + acc[i]; |
| acc[i] = BCached[1] * ACached.y + acc[i]; |
| acc[i] = BCached[2] * ACached.z + acc[i]; |
| acc[i] = BCached[3] * ACached.w + acc[i]; |
| } |
| } |
| |
| workgroupBarrier(); |
| } |
| |
| for (var innerRow : u32 = 0u; innerRow < RowPerThread; innerRow = innerRow + 1u) { |
| mm_write(globalRow + innerRow, |
| globalCol, |
| acc[innerRow]); |
| } |
| })"; |
| |
| const std::string& kMatMulVec4OneDimensionalSharedArray = |
| kMatMulVec4Header + kMatMulVec4SharedArray1D + kMatMulVec4BodyPart1 + |
| kMatMulVec4BodyPart2Array1D + kMatMulVec4BodyPart3; |
| |
| const std::string& kMatMulVec4TwoDimensionalSharedArray = |
| kMatMulVec4Header + kMatMulVec4SharedArray2D + kMatMulVec4BodyPart1 + |
| kMatMulVec4BodyPart2Array2D + kMatMulVec4BodyPart3; |
| |
| constexpr unsigned int kNumIterations = 50; |
| |
| enum class MatMulMethod { |
| MatMulFloatOneDimSharedArray, |
| MatMulFloatTwoDimSharedArray, |
| MatMulVec4OneDimSharedArray, |
| MatMulVec4TwoDimSharedArray |
| }; |
| |
| std::ostream& operator<<(std::ostream& ostream, const MatMulMethod& matMulMethod) { |
| switch (matMulMethod) { |
| case MatMulMethod::MatMulFloatOneDimSharedArray: |
| ostream << "MatMulFloatOneDimSharedArray"; |
| break; |
| case MatMulMethod::MatMulFloatTwoDimSharedArray: |
| ostream << "MatMulFloatTwoDimSharedArray"; |
| break; |
| case MatMulMethod::MatMulVec4OneDimSharedArray: |
| ostream << "MatMulVec4OneDimSharedArray"; |
| break; |
| case MatMulMethod::MatMulVec4TwoDimSharedArray: |
| ostream << "MatMulVec4TwoDimSharedArray"; |
| break; |
| } |
| return ostream; |
| } |
| |
| using DimAOuter = uint32_t; |
| using DimInner = uint32_t; |
| using DimBOuter = uint32_t; |
| DAWN_TEST_PARAM_STRUCT(ShaderRobustnessParams, MatMulMethod, DimAOuter, DimInner, DimBOuter); |
| |
| // Test the execution time of matrix multiplication (A [dimAOuter, dimInner] * B [dimInner, |
| // dimBOuter]) on the GPU and see the difference between robustness on and off. |
| class ShaderRobustnessPerf : public DawnPerfTestWithParams<ShaderRobustnessParams> { |
| public: |
| ShaderRobustnessPerf() |
| : DawnPerfTestWithParams(kNumIterations, 1), |
| mDimAOuter(GetParam().mDimAOuter), |
| mDimInner(GetParam().mDimInner), |
| mDimBOuter(GetParam().mDimBOuter) {} |
| ~ShaderRobustnessPerf() override = default; |
| |
| void SetUp() override; |
| |
| private: |
| void Step() override; |
| |
| wgpu::BindGroup mBindGroup; |
| wgpu::ComputePipeline mPipeline; |
| uint32_t mDimAOuter; |
| uint32_t mDimInner; |
| uint32_t mDimBOuter; |
| }; |
| |
| void ShaderRobustnessPerf::SetUp() { |
| DawnPerfTestWithParams<ShaderRobustnessParams>::SetUp(); |
| |
| 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(); |
| if (SupportsTimestampQuery()) { |
| RecordBeginTimestamp(encoder); |
| } |
| wgpu::ComputePassEncoder pass = encoder.BeginComputePass(); |
| pass.SetPipeline(mPipeline); |
| pass.SetBindGroup(0, mBindGroup); |
| for (unsigned int i = 0; i < kNumIterations; ++i) { |
| pass.DispatchWorkgroups(ceil(static_cast<float>(mDimBOuter) / float{kTileSize}), |
| ceil(static_cast<float>(mDimAOuter) / float{kTileSize}), 1); |
| } |
| pass.End(); |
| if (SupportsTimestampQuery()) { |
| RecordEndTimestampAndResolveQuerySet(encoder); |
| } |
| |
| commands = encoder.Finish(); |
| } |
| |
| queue.Submit(1, &commands); |
| |
| if (SupportsTimestampQuery()) { |
| ComputeGPUElapsedTime(); |
| } |
| } |
| |
| 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}); |
| |
| } // anonymous namespace |
| } // namespace dawn |