The Application Slowdown Model: Quantifying and Controlling the Impact of Inter-Application Interference at Shared Caches and Main Memory

In a multi-core system, interference at shared resources (such as caches and main memory) slows down applica-tions running on different cores. Accurately estimating the slowdown of each application has several benefits: e.g., it can enable shared resource allocation in a man-ner that avoids unfair application slowdowns or provides slowdown guarantees. Unfortunately, prior works on es-timating slowdowns either lead to inaccurate estimates, do not take into account shared caches, or rely on a priori application knowledge. This severely limits their applicability. In this work, we propose the Application Slowdown Model (ASM), a new technique that accurately estimates application slowdowns due to interference at both th