Training Models Too Big for One GPU | ZeRO & FSDP
How do you train a model that does not fit on one GPU?
In this video, we cover how GPUs represent and store real numbers, mixed-precision training, and the Zero Redundancy Optimizer (ZeRO) and FSDP to reduce memory redundancy in data parallelism.
Chapters
0:00 How a model learns
0:55 Adam optimizer
1:56 How a computer stores real numbers
11:40 The memory constraint
12:40 Data parallelism
13:21 How GPUs sync their gradients
16:07 ZeRO stage 1 and 2: shard the optimizer states, then the gradients
19:27 ZeRO stage 3: shard the weights
21:28 FSDP: the same schedule one unit at a time
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