Audience

Data scientists, AI engineers, and organizations interested in a solution to accelerate training and deployment while minimizing operational overhead

About Amazon SageMaker HyperPod

Amazon SageMaker HyperPod is a purpose-built, resilient compute infrastructure that simplifies and accelerates the development of large AI and machine-learning models by handling distributed training, fine-tuning, and inference across clusters with hundreds or thousands of accelerators, including GPUs and AWS Trainium chips. It removes the heavy lifting involved in building and managing ML infrastructure by providing persistent clusters that automatically detect and repair hardware failures, automatically resume workloads, and optimize checkpointing to minimize interruption risk, enabling months-long training jobs without disruption. HyperPod offers centralized resource governance; administrators can set priorities, quotas, and task-preemption rules so compute resources are allocated efficiently among tasks and teams, maximizing utilization and reducing idle time. It also supports “recipes” and pre-configured settings to quickly fine-tune or customize foundation models.

Integrations

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Company Information

Amazon
Founded: 1994
United States
aws.amazon.com/sagemaker/ai/hyperpod/

Videos and Screen Captures

Amazon SageMaker HyperPod Screenshot 1
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Product Details

Platforms Supported
Cloud
Training
Documentation
Live Online
Webinars
Videos
Support
Phone Support
Online

Amazon SageMaker HyperPod Frequently Asked Questions

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Amazon SageMaker HyperPod Product Features