Title: SAGA: Workflow-Atomic Scheduling for AI Agent Inference on GPU Clusters

Source: http://arxiv.org/abs/2605.00528v1

Summary:

SAGA represents a foundational breakthrough in agentic AI systems by transitioning from request-level to workflow-atomic scheduling for GPU inference. By capturing and optimizing for the chained structure of agentic tasks, it significantly reduces latency and resource overhead, enabling the scaling of complex, multi-step AI agents.