What about GPU Architecture makes them superior for training neural networks over CPUs?

Question

In ML/AI, GPUs are used to train neural networks of various sizes. They are vastly superior to training on CPUs. Why is this?

In: 679

Answer 1

GPUs are optimized for tasks where you need to perform the same operation on thousands of objects at the same time because they usually do very similar calculations for every pixel of the screen. Neural network training gives you more or less this: you need to recalculate parameters for each neuron with mostly the same formula.

CPUs only have a few cores so they would have to recalculate these neurons one by one instead of hundreds at a time, greatly reducing the speed.

Answer 2

GPUs are optimized for tasks where you need to perform the same operation on thousands of objects at the same time because they usually do very similar calculations for every pixel of the screen. Neural network training gives you more or less this: you need to recalculate parameters for each neuron with mostly the same formula.

CPUs only have a few cores so they would have to recalculate these neurons one by one instead of hundreds at a time, greatly reducing the speed.