# Amazon — Multi-Region training with Amazon SageMaker HyperPod and Qumulo

- Company: Amazon (amazon.com)
- Announced: 2026-09-25T15:49:44+00:00
- Category: not stated
- Coverage: not counted
- Announcement: no
- Group: routine
- Source: https://aws.amazon.com/blogs/machine-learning/multi-region-training-with-amazon-sagemaker-hyperpod-and-qumulo/
- Record: https://forck.live/items/13879-multi-region-training-with-amazon-sagemaker-hyperpod-and-qumulo
- Subject: Bedrock / Nova

Amazon published a solution architecture pairing SageMaker HyperPod with Qumulo's Cloud Data Fabric to enable cross-Region training without copying data. Validation showed a spoke cluster in us-west-2 reading data from a hub in us-east-2 matched the hub's throughput of 115–117 samples/sec after a warmup period, achieving 98–100% GPU utilization. The post describes the architecture, NeuralCache predictive caching, and validation results from a 1.02 billion-parameter LLaMA v3 training run.

## Evidence

Verbatim from https://aws.amazon.com/blogs/machine-learning/multi-region-training-with-amazon-sagemaker-hyperpod-and-qumulo/:

> A HyperPod cluster running in a different Region from its data reaches the same throughput as a cluster co-located with the data (115–117 samples/sec) with no additional data orchestration needed.

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