Thanks for your answer.
I have a lot of existing code in Numpy which I am considering porting to a different library which can use my non-CUDA GPU. Since PyTorch cannot use it, is there any way in which it can be faster than Numpy in doing deep learning computations?
My code is a neural network to train convolutional and sparse MLP layers on datasets such as MNIST and CIFAR.