AI RESEARCH
SemaTune: Semantic-Aware Online OS Tuning with Large Language Models
arXiv CS.AI
•
ArXi:2605.15026v1 Announce Type: cross Online OS tuning can improve long-running services, but existing controllers are poorly matched to live hosts. They treat scheduler, power, memory, and I/O controls as black-box variables and optimize a scalar reward. This view ignores cross-knob policy structure, breaks down when application metrics are unavailable, and can send a running service into degraded regions that persist after the bad setting is removed. We present SemaTune, a host-side framework for steady-state OS tuning with bounded language-model guidance.