Maximize GPU utilization with SageMaker HyperPod task governance | AWS OnAir re:Invent 2024

Teams across organizations are training new models, fine-tuning them with their data, and running inference at scale, all of which requires timely access to accelerated compute resources. Given the overwhelming demand and a finite budget, organizations are unable to allocate accelerated compute resources to each project and task when needed. In this session, learn about how Amazon SageMaker HyperPod’s new governance capability helps dynamically run FM development tasks such as training, fine-tuning, or inference on shared compute resources, ensuring the most important FM development projects get completed on time, while avoiding cost-overruns due to under-utilized compute resources.
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