COSC-4P80-Assignment-2/lib/eigen-3.4.0/unsupported/doc/examples/SYCL/CwiseMul.cpp

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2024-10-21 16:42:03 -04:00
#include <iostream>
#define EIGEN_USE_SYCL
#include <unsupported/Eigen/CXX11/Tensor>
using Eigen::array;
using Eigen::SyclDevice;
using Eigen::Tensor;
using Eigen::TensorMap;
int main()
{
using DataType = float;
using IndexType = int64_t;
constexpr auto DataLayout = Eigen::RowMajor;
auto devices = Eigen::get_sycl_supported_devices();
const auto device_selector = *devices.begin();
Eigen::QueueInterface queueInterface(device_selector);
auto sycl_device = Eigen::SyclDevice(&queueInterface);
// create the tensors to be used in the operation
IndexType sizeDim1 = 3;
IndexType sizeDim2 = 3;
IndexType sizeDim3 = 3;
array<IndexType, 3> tensorRange = {{sizeDim1, sizeDim2, sizeDim3}};
// initialize the tensors with the data we want manipulate to
Tensor<DataType, 3,DataLayout, IndexType> in1(tensorRange);
Tensor<DataType, 3,DataLayout, IndexType> in2(tensorRange);
Tensor<DataType, 3,DataLayout, IndexType> out(tensorRange);
// set up some random data in the tensors to be multiplied
in1 = in1.random();
in2 = in2.random();
// allocate memory for the tensors
DataType * gpu_in1_data = static_cast<DataType*>(sycl_device.allocate(in1.size()*sizeof(DataType)));
DataType * gpu_in2_data = static_cast<DataType*>(sycl_device.allocate(in2.size()*sizeof(DataType)));
DataType * gpu_out_data = static_cast<DataType*>(sycl_device.allocate(out.size()*sizeof(DataType)));
//
TensorMap<Tensor<DataType, 3, DataLayout, IndexType>> gpu_in1(gpu_in1_data, tensorRange);
TensorMap<Tensor<DataType, 3, DataLayout, IndexType>> gpu_in2(gpu_in2_data, tensorRange);
TensorMap<Tensor<DataType, 3, DataLayout, IndexType>> gpu_out(gpu_out_data, tensorRange);
// copy the memory to the device and do the c=a*b calculation
sycl_device.memcpyHostToDevice(gpu_in1_data, in1.data(),(in1.size())*sizeof(DataType));
sycl_device.memcpyHostToDevice(gpu_in2_data, in2.data(),(in2.size())*sizeof(DataType));
gpu_out.device(sycl_device) = gpu_in1 * gpu_in2;
sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.size())*sizeof(DataType));
sycl_device.synchronize();
// print out the results
for (IndexType i = 0; i < sizeDim1; ++i) {
for (IndexType j = 0; j < sizeDim2; ++j) {
for (IndexType k = 0; k < sizeDim3; ++k) {
std::cout << "device_out" << "(" << i << ", " << j << ", " << k << ") : " << out(i,j,k)
<< " vs host_out" << "(" << i << ", " << j << ", " << k << ") : " << in1(i,j,k) * in2(i,j,k) << "\n";
}
}
}
printf("c=a*b Done\n");
}