#gpu-resource-management

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DevOps
fromInfoQ
1 week ago

Running Ray at Scale on AKS

Microsoft and Anyscale provide guidance for running managed Ray service on Azure Kubernetes Service, addressing GPU capacity limits, ML storage challenges, and credential expiry issues through multi-cluster, multi-region deployment strategies.
fromInfoQ
3 months ago

NVIDIA Dynamo Addresses Multi-Node LLM Inference Challenges

This challenge is sparking innovations in the inference stack. That's where Dynamo comes in. Dynamo is an open-source framework for distributed inference. It manages execution across GPUs and nodes. It breaks inference into phases, like prefill and decode. It also separates memory-bound and compute-bound tasks. Plus, it dynamically manages GPU resources to boost usage and keep latency low. Dynamo allows infrastructure teams to scale inference capacity responsively, handling demand spikes without permanently overprovisioning expensive GPU resources.
Artificial intelligence
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