What are the differences between multiprocessing and threading in AI?

What are the differences between multiprocessing and threading in AI?

Multiprocessing involves multiple processes running independently, while threading uses multiple threads within a single process. In AI, multiprocessing can handle CPU-bound tasks better, while threading is more efficient for I/O-bound tasks.

Can you give examples of when to use each?

Sure! Use multiprocessing for tasks like training large models that require heavy computation. Use threading for tasks like data loading or making API calls where waiting is involved.

What are the advantages of using multiprocessing?

Multiprocessing can utilize multiple CPU cores, improving performance for CPU-intensive tasks and avoiding the Global Interpreter Lock (GIL) in Python.

Are there any downsides to using multiprocessing?

Yes, multiprocessing can have higher memory usage and overhead due to process creation and inter-process communication.