SAGA reduces AI agent task completion time by 1.64x on 64-GPU clusters by scheduling at the full workflow level with execution graphs, affinity batching, and completion-time fairness.
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VISPA adds voluntary energy monitoring, green-window job scheduling, and user feedback systems to a physics cluster to cut greenhouse-gas emissions through greater resource awareness.
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SAGA: Workflow-Atomic Scheduling for AI Agent Inference on GPU Clusters
SAGA reduces AI agent task completion time by 1.64x on 64-GPU clusters by scheduling at the full workflow level with execution graphs, affinity batching, and completion-time fairness.
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Enabling users to work sustainably on shared institute computing resources
VISPA adds voluntary energy monitoring, green-window job scheduling, and user feedback systems to a physics cluster to cut greenhouse-gas emissions through greater resource awareness.