Exploiting Task Temperature Profiling in Temperature-Aware Task Scheduling for Computational Clusters

Abstract

Many years of CMOS technology scaling have resulted in increased power densities and higher core temperatures. Power and temperature concerns are now considered to be a primary challenge for continued scaling and long-term processor reliability. While solutions for low-power and low-temperature circuits and microarchitectures have been studied for many years, temperature-awareness at the computational cluster level is a relatively new problem. To address this problem, we introduce a temperature-aware task scheduler based on task temperature profiling. We study the task characteristics and temperature profiles for a subset of SPEC’2K benchmarks. We exploit these profiles and suggest several scheduling algorithms aimed at achieving lower cluster temperature. Our findings show a clear trade-off between the overall queue servicing time and the cluster peak temperature. Whether the temperature reductions achieved are worth the extra delay is left to the designer/user to decide based on the case by case performance restrictions and temperature limitations.