Multi-Region training with Amazon SageMaker HyperPod and Qumulo

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With Amazon SageMaker HyperPod and Qumulo , you can place training compute in one AWS Region and keep your dataset in another. Training large AI models requires massive GPU capacity, but your ideal compute resources and your training data don’t always reside in the same AWS Region. Accessing data across Regions adds network latency and transfer costs. Teams face a choice: either replicate petabytes of data across Regions, or absorb cross-Region latency on every read and accept slower training.…