Parallelization

Parallelization is the practice of doing many computations at the same time instead of one after another.

In AI:

• It’s essential for both training and inference.
• GPUs are built to run thousands of operations in parallel, which is why they’re central to modern AI.
• As models get larger and more complex, spreading work across many chips and machines is crucial for speed and cost efficiency.
• Optimizing how to parallelize AI workloads has become a major research area in itself.