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

Because GPUs are designed specifically to process graphics, they are REALLY good at manipulating a mathematical object called a “matrix” which we can think of as a box of numbers. CPU’s are designed for general purpose calculations, and are thus not specialised.

The majority of neural nets are built in such a way that they may be written down in terms of these matrices (plural for matrix), which makes GPUs much better at calculating operations than CPUs.

Source: I’m a mathematician with an interest in machine learning.

Answer 2

Because GPUs are designed specifically to process graphics, they are REALLY good at manipulating a mathematical object called a “matrix” which we can think of as a box of numbers. CPU’s are designed for general purpose calculations, and are thus not specialised.

The majority of neural nets are built in such a way that they may be written down in terms of these matrices (plural for matrix), which makes GPUs much better at calculating operations than CPUs.

Source: I’m a mathematician with an interest in machine learning.