Modeling the Effects on Power and Performance from Memory Interference of Co-located Applications in Multicore Systems

Abstract — In this study, we analyze interference trends when co-running multiple applications possessing varying degrees of memory intensity on multi-core processors. We conduct tests with PARSEC benchmark applications and explore energy consumption, execution times, and main memory accesses when interfering applications share last-level cache. We also explore how co-running applications are impacted when the processor frequency is modified using dynamic voltage and frequency scaling (DVFS). A portable and lightweight testing framework is presented and results are shown for experiments conducted on an Intel i7 quad-core system. It is shown that the degree of degradation due to co-location interference on execution time is highly dependent on the types and number of applications co-located on cores that share the last-level cache