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

ML/AI is basically just a lot of complicated calculations and operations.

GPUs can do a lot of math parallelly, at the same time. It is not ‘smart’. You can consider it analogous to the “nerd” kid in the class.
The CPU on the other hand is analogous to the “life-smart” kid in the class, meaning it can do various other tasks (like controlling what to send to the monitor/display, what data to retrieve from the storages etc.) along with some complicated math. As a result, it takes more time to solve the math but it does solve them eventually, because while they are not *that* nerdy, they still are studious and capable if need be.

Answer 2

ML/AI is basically just a lot of complicated calculations and operations.

GPUs can do a lot of math parallelly, at the same time. It is not ‘smart’. You can consider it analogous to the “nerd” kid in the class.
The CPU on the other hand is analogous to the “life-smart” kid in the class, meaning it can do various other tasks (like controlling what to send to the monitor/display, what data to retrieve from the storages etc.) along with some complicated math. As a result, it takes more time to solve the math but it does solve them eventually, because while they are not *that* nerdy, they still are studious and capable if need be.