Mise: Providing performance predictability and improving fairness in shared main memory systems

Applications running concurrently on a multicore system in-terfere with each other at the main memory. This interference can slow down diUerent applications diUerently. Accurately es-timating the slowdown of each application in such a system can enable mechanisms that can enforce quality-of-service. While much prior work has focused on mitigating the performance degradation due to inter-application interference, there is lit-tle work on estimating slowdown of individual applications in a multi-programmed environment. Our goal in this work is to build such an estimation scheme. To this end, we present our simple Memory-Interference-induced Slowdown Estimation (MISE) model that estimates slowdowns caused by memory interference. We build our model based on two observations. First, the performance of a memory