Could you explain your use case a bit more?
If you have separate computations, you could use each GPU to perform a single op:
res0 = torch.matmul(x.to('cuda:0'), y.to('cuda:0')
res1 = torch.matmul(x.to('cuda:1'), y.to('cuda:1')

Another approach would be to use nn.DataParallel in case you would like to send data chunks to each GPU and perform the same operations.