SageMaker Model Parallelism: Achieving Faster and more Efficient Training with PyTorch FSDP
Introduction¶ Training deep learning models at scale can be a challenging task. As models grow larger, the memory requirements for training increase exponentially. Furthermore, distributing the workload across multiple accelerators in a cluster introduces additional complexities in terms of communication and synchronization. To address these challenges, Amazon SageMaker now offers the SageMaker Model Parallelism feature, …