Why and when to use graphics cards?

Graphics cards (GPU) are used to accelerate computations, especially when tasks can be parallelized. In machine learning and artificial intelligence, they are used for training neural networks because they allow for the simultaneous processing of thousands of matrix and vector operations, which is much faster than on a CPU.

You should use graphics cards when:

• Large volumes of data are processed.
• Models have a complex architecture with many parameters.
• There is a need to speed up training or inference.

For example, when training deep neural networks on TensorFlow or PyTorch, using a GPU can reduce training time from days to hours.