L12b Parallelization -- Instructor: Wilson Yan - YouTube
This video explains how to train massive AI models (like GPT-3) by splitting the work across many computer chips (GPUs) because the models are too big for just one (0:09-0:24). Think of it like trying to build a giant LEGO set: it's too much for one person, so you split the instructions into pieces and have a whole team work on different parts at the same time to finish it faster. Here are the main ways they split the work: The biggest challenge is that chips constantly need to 'talk' to each other to share their progress. If this communication is slow, it slows down the whole project (1:05-1:32). Model sharding is a technique used to train massive AI models by breaking them into smaller pieces, or shards, and distributing those pieces across multiple computer chips (GPUs or TPUs) (0:09-0:24, 3:35-3:51). Since modern models like GPT-3 have billions of parameters, they are too large to fit into the memory of a single chip. Sharding solves this by: Essentially, it turns a task that is im