Dynamic Colocation Policies with Reinforcement Learning
Yuhao Li, Dan Sun, Benjamin C. Lee · ACM Transactions on Architecture and Code Optimization · 2020
We draw on reinforcement learning frameworks to design and implement an adaptive controller for managing resource contention. During runtime, the controller observes the dynamic system conditions and optimizes control policies that satisfy latency targets yet improve server utilization. We evaluate a physical prototype that guarantees 95th percentile latencies for a search engine and improves server utilization by up to 70%, compared to exclusively reserving servers for interactive services, for varied batch workloads in machine learning.