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63 lines
2.5 KiB
63 lines
2.5 KiB
#include <iostream> |
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#define EIGEN_USE_SYCL |
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#include <unsupported/Eigen/CXX11/Tensor> |
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using Eigen::array; |
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using Eigen::SyclDevice; |
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using Eigen::Tensor; |
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using Eigen::TensorMap; |
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int main() |
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{ |
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using DataType = float; |
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using IndexType = int64_t; |
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constexpr auto DataLayout = Eigen::RowMajor; |
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auto devices = Eigen::get_sycl_supported_devices(); |
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const auto device_selector = *devices.begin(); |
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Eigen::QueueInterface queueInterface(device_selector); |
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auto sycl_device = Eigen::SyclDevice(&queueInterface); |
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// create the tensors to be used in the operation |
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IndexType sizeDim1 = 3; |
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IndexType sizeDim2 = 3; |
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IndexType sizeDim3 = 3; |
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array<IndexType, 3> tensorRange = {{sizeDim1, sizeDim2, sizeDim3}}; |
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// initialize the tensors with the data we want manipulate to |
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Tensor<DataType, 3,DataLayout, IndexType> in1(tensorRange); |
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Tensor<DataType, 3,DataLayout, IndexType> in2(tensorRange); |
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Tensor<DataType, 3,DataLayout, IndexType> out(tensorRange); |
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// set up some random data in the tensors to be multiplied |
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in1 = in1.random(); |
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in2 = in2.random(); |
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// allocate memory for the tensors |
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DataType * gpu_in1_data = static_cast<DataType*>(sycl_device.allocate(in1.size()*sizeof(DataType))); |
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DataType * gpu_in2_data = static_cast<DataType*>(sycl_device.allocate(in2.size()*sizeof(DataType))); |
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DataType * gpu_out_data = static_cast<DataType*>(sycl_device.allocate(out.size()*sizeof(DataType))); |
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// |
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TensorMap<Tensor<DataType, 3, DataLayout, IndexType>> gpu_in1(gpu_in1_data, tensorRange); |
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TensorMap<Tensor<DataType, 3, DataLayout, IndexType>> gpu_in2(gpu_in2_data, tensorRange); |
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TensorMap<Tensor<DataType, 3, DataLayout, IndexType>> gpu_out(gpu_out_data, tensorRange); |
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// copy the memory to the device and do the c=a*b calculation |
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sycl_device.memcpyHostToDevice(gpu_in1_data, in1.data(),(in1.size())*sizeof(DataType)); |
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sycl_device.memcpyHostToDevice(gpu_in2_data, in2.data(),(in2.size())*sizeof(DataType)); |
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gpu_out.device(sycl_device) = gpu_in1 * gpu_in2; |
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sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.size())*sizeof(DataType)); |
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sycl_device.synchronize(); |
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// print out the results |
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for (IndexType i = 0; i < sizeDim1; ++i) { |
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for (IndexType j = 0; j < sizeDim2; ++j) { |
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for (IndexType k = 0; k < sizeDim3; ++k) { |
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std::cout << "device_out" << "(" << i << ", " << j << ", " << k << ") : " << out(i,j,k) |
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<< " vs host_out" << "(" << i << ", " << j << ", " << k << ") : " << in1(i,j,k) * in2(i,j,k) << "\n"; |
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} |
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} |
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} |
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printf("c=a*b Done\n"); |
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}
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