forked from jiuyuan/InfiniTensor
Add comments in conv benchmark
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97970c5d94
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608f997042
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@ -31,11 +31,12 @@ const char mode_name[2][50] = {
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};
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int main() {
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// Benchmark Settings
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int warmupRounds = 50;
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int timingRounds = 100;
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DataType dtype = DataType::Float32;
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// cudnn Conv Configurations
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cudnnConvolutionMode_t convMode = CUDNN_CROSS_CORRELATION;
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cudnnConvolutionFwdAlgo_t convAlgo = CUDNN_CONVOLUTION_FWD_ALGO_IMPLICIT_PRECOMP_GEMM;
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float alpha = 1.f, beta = 0.f;
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@ -63,19 +64,21 @@ int main() {
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int DILATION_HEIGHT = 1;
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int DILATION_WIDTH = 1;
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// Get input size
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size_t inputSize = 1;
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for (auto dim: INPUT_SHAPE) {
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inputSize *= dim;
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}
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size_t inputSizeInBytes = inputSize * sizeof(dtype);
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// Get kernel size
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size_t kernelSize = 1;
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for (auto dim: KERNEL_SHAPE) {
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kernelSize *= dim;
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}
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size_t kernelSizeInBytes = kernelSize * sizeof(dtype);
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// Init time
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// Init time variables
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double time_memcpy_htod = 0.0, time_memcpy_dtoh = 0.0;
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double time_op = 0.0;
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@ -83,7 +86,7 @@ int main() {
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Runtime cpuRuntime = NativeCpuRuntimeObj::getInstance();
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auto cudaRuntime = make_ref<CudaRuntimeObj>();
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// Build input data on CPU
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// Build input data and kernel on CPU
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Tensor inputCpu =
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make_ref<TensorObj>(INPUT_SHAPE, dtype, cpuRuntime);
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inputCpu->dataMalloc();
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@ -94,7 +97,7 @@ int main() {
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kernelCpu->dataMalloc();
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kernelCpu->setData(RandomGenerator());
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// Build input data on GPU
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// Build input data and kernel on GPU
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Tensor inputGpu =
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make_ref<TensorObj>(INPUT_SHAPE, dtype, cudaRuntime);
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inputGpu->dataMalloc();
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@ -115,26 +118,27 @@ int main() {
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int channelsPerGrp = INPUT_CHANNELS / NUM_GROUPS;
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// get inputs
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// Build cudnn descriptors
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// input descriptor
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cudnnTensorDescriptor_t inDesc;
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checkCudnnError(cudnnCreateTensorDescriptor(&inDesc));
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checkCudnnError(cudnnSetTensor4dDescriptor(
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inDesc, CUDNN_TENSOR_NCHW, CUDNN_DATA_FLOAT, n, c, h, w));
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// get kernels
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// kernel descriptor
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cudnnFilterDescriptor_t knDesc;
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checkCudnnError(cudnnCreateFilterDescriptor(&knDesc));
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checkCudnnError(cudnnSetFilter4dDescriptor(knDesc, CUDNN_DATA_FLOAT,
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CUDNN_TENSOR_NCHW, f,
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channelsPerGrp, r, s));
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// get bias
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// bias descriptor
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// cudnnTensorDescriptor_t biasDesc;
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// checkCudnnError(cudnnCreateTensorDescriptor(&biasDesc));
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// checkCudnnError(cudnnSetTensor4dDescriptor(
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// biasDesc, CUDNN_TENSOR_NCHW, CUDNN_DATA_FLOAT, 1, f, 1, 1));
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// get convlution descriptor
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// convlution descriptor
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cudnnConvolutionDescriptor_t convDesc;
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checkCudnnError(cudnnCreateConvolutionDescriptor(&convDesc));
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checkCudnnError(cudnnSetConvolution2dDescriptor(
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@ -144,16 +148,19 @@ int main() {
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checkCudnnError(cudnnSetConvolutionGroupCount(convDesc, NUM_GROUPS));
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}
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// Get output shape
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int outn, outc, outh, outw;
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checkCudnnError(cudnnGetConvolution2dForwardOutputDim(
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convDesc, inDesc, knDesc, &outn, &outc, &outh, &outw));
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// Build output descriptor
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cudnnTensorDescriptor_t outDesc;
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checkCudnnError(cudnnCreateTensorDescriptor(&outDesc));
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checkCudnnError(cudnnSetTensor4dDescriptor(outDesc, CUDNN_TENSOR_NCHW,
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CUDNN_DATA_FLOAT, outn, outc,
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outh, outw));
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// Get output size
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Shape OUTPUT_SHAPE = {outn, outc, outh, outw};
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size_t outputSize = 1;
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for (auto dim: OUTPUT_SHAPE) {
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@ -171,6 +178,7 @@ int main() {
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make_ref<TensorObj>(OUTPUT_SHAPE, dtype, cudaRuntime);
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outputGpu->dataMalloc();
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// Get workspace size
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size_t workspaceSize = 0;
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checkCudnnError(cudnnGetConvolutionForwardWorkspaceSize(
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cudaRuntime->cudnnHandle(), inDesc, knDesc, convDesc,
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@ -178,6 +186,7 @@ int main() {
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CudaPtr workspace = cudaRuntime->getWorkspace(workspaceSize);
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// Do forward
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time_op += timeit(
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[&]() {
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cudnnConvolutionForward(cudaRuntime->cudnnHandle(), &alpha,
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@ -197,6 +206,7 @@ int main() {
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checkCudnnError(cudnnDestroyFilterDescriptor(knDesc));
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checkCudnnError(cudnnDestroyTensorDescriptor(inDesc));
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// Do memcpy device to host
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time_memcpy_dtoh += timeit(
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[&]() {
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outputCpu = outputGpu->clone(cpuRuntime);
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