1 #include <iostream>
2 #define EIGEN_USE_SYCL
3 #include <unsupported/Eigen/CXX11/Tensor>
4
5 using Eigen::array;
6 using Eigen::SyclDevice;
7 using Eigen::Tensor;
8 using Eigen::TensorMap;
9
main()10 int main()
11 {
12 using DataType = float;
13 using IndexType = int64_t;
14 constexpr auto DataLayout = Eigen::RowMajor;
15
16 auto devices = Eigen::get_sycl_supported_devices();
17 const auto device_selector = *devices.begin();
18 Eigen::QueueInterface queueInterface(device_selector);
19 auto sycl_device = Eigen::SyclDevice(&queueInterface);
20
21 // create the tensors to be used in the operation
22 IndexType sizeDim1 = 3;
23 IndexType sizeDim2 = 3;
24 IndexType sizeDim3 = 3;
25 array<IndexType, 3> tensorRange = {{sizeDim1, sizeDim2, sizeDim3}};
26
27 // initialize the tensors with the data we want manipulate to
28 Tensor<DataType, 3,DataLayout, IndexType> in1(tensorRange);
29 Tensor<DataType, 3,DataLayout, IndexType> in2(tensorRange);
30 Tensor<DataType, 3,DataLayout, IndexType> out(tensorRange);
31
32 // set up some random data in the tensors to be multiplied
33 in1 = in1.random();
34 in2 = in2.random();
35
36 // allocate memory for the tensors
37 DataType * gpu_in1_data = static_cast<DataType*>(sycl_device.allocate(in1.size()*sizeof(DataType)));
38 DataType * gpu_in2_data = static_cast<DataType*>(sycl_device.allocate(in2.size()*sizeof(DataType)));
39 DataType * gpu_out_data = static_cast<DataType*>(sycl_device.allocate(out.size()*sizeof(DataType)));
40
41 //
42 TensorMap<Tensor<DataType, 3, DataLayout, IndexType>> gpu_in1(gpu_in1_data, tensorRange);
43 TensorMap<Tensor<DataType, 3, DataLayout, IndexType>> gpu_in2(gpu_in2_data, tensorRange);
44 TensorMap<Tensor<DataType, 3, DataLayout, IndexType>> gpu_out(gpu_out_data, tensorRange);
45
46 // copy the memory to the device and do the c=a*b calculation
47 sycl_device.memcpyHostToDevice(gpu_in1_data, in1.data(),(in1.size())*sizeof(DataType));
48 sycl_device.memcpyHostToDevice(gpu_in2_data, in2.data(),(in2.size())*sizeof(DataType));
49 gpu_out.device(sycl_device) = gpu_in1 * gpu_in2;
50 sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.size())*sizeof(DataType));
51 sycl_device.synchronize();
52
53 // print out the results
54 for (IndexType i = 0; i < sizeDim1; ++i) {
55 for (IndexType j = 0; j < sizeDim2; ++j) {
56 for (IndexType k = 0; k < sizeDim3; ++k) {
57 std::cout << "device_out" << "(" << i << ", " << j << ", " << k << ") : " << out(i,j,k)
58 << " vs host_out" << "(" << i << ", " << j << ", " << k << ") : " << in1(i,j,k) * in2(i,j,k) << "\n";
59 }
60 }
61 }
62 printf("c=a*b Done\n");
63 }
64