---
format: "aidr-story-markdown/v1"
id: "c619830bcd21454592c2b541f5d4526015a812e9e7b91662b6b7eda447cf8016"
canonical_url: "https://aidr.today/c619830b?lang=en"
title: "Multi-Region training with Amazon SageMaker HyperPod and Qumulo"
lang: "en"
requested_lang: "en"
available_langs: ["en","vi"]
translation_fallback: null
fallback_fields: []
published_at: "2026-09-25T15:49:44.000Z"
category: "Infra"
topics: ["amazon","llm"]
source_urls: ["https://aws.amazon.com/blogs/machine-learning/multi-region-training-with-amazon-sagemaker-hyperpod-and-qumulo/","https://aws.amazon.com/blogs/machine-learning/accelerate-multimodal-rl-training-with-skyrl-on-amazon-sagemaker-hyperpod/"]
summary: "Amazon SageMaker HyperPod and Cloud Native Qumulo let you place training compute in one AWS Region while keeping your dataset in another. This post shares the architecture and validation results from a cross-Region training run, where a remote cluster matched a co-located cluster's throughput after a brief NeuralCache warmup."
---

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

> [Open the canonical story](<https://aidr.today/c619830b?lang=en>)

**Published:** 2026-09-25T15:49:44.000Z
**Category:** Infra
**Topics:** amazon, llm

## Summary

Amazon SageMaker HyperPod and Cloud Native Qumulo let you place training compute in one AWS Region while keeping your dataset in another\. This post shares the architecture and validation results from a cross\-Region training run, where a remote cluster matched a co\-located cluster's throughput after a brief NeuralCache warmup\.

## Sources

- [Story source](<https://aws.amazon.com/blogs/machine-learning/multi-region-training-with-amazon-sagemaker-hyperpod-and-qumulo/>)
- [Story source](<https://aws.amazon.com/blogs/machine-learning/accelerate-multimodal-rl-training-with-skyrl-on-amazon-sagemaker-hyperpod/>)