Infrastructure
Distributed Training
Infrastructure· Advanced
Definition
Training machine learning models across multiple GPUs or machines in parallel — using techniques like data parallelism (splitting batches), model parallelism (splitting layers), and pipeline parallelism (splitting the computation graph). Required for training models that don't fit on a single GPU.
Enterprise Context
All frontier LLMs are trained using distributed training across thousands of GPUs. Understanding distributed training is essential for organizations running proprietary model training programs.
Tags
#training#scale#hardware
MS
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