SwarmX: Agentic Scheduling for Low-Latency Agentic Systems

SwarmX is a newly proposed agentic scheduling system designed to optimize low-latency AI applications that involve multiple model calls and tool executions. It employs scheduling-specific neural predictors that analyze prompt semantics and device characteristics to make tail-aware scheduling decisions, effectively reducing tail latency by up to 61.5% and achieving up to 2x the throughput compared to existing production schedulers. This innovation is significant for practitioners as it enhances the efficiency of GPU-CPU clusters in handling complex agentic workflows, facilitating improved performance in real-time AI applications.