DyCa: Dynamically Adaptable Cache Bypassing Mechanism

Abstract

As the number of cores increases, more cores and threads share the Last-Level Cache (LLC), which consumes a large portion of the chip’s total power and area. Therefore, sophisticated solutions must guarantee the best resource usage addressing cache conflicts and cache pollution problems. This work exploits the knowledge that many applications present poor temporal and spatial locality. Thus, an adaptive cache mechanism can benefit such applications, improving general system performance and decreasing energy consumption. In this paper, we propose an online and application-aware predictor to adapt the use of LLC. As a result, DyCa shows up to 22% and 21% performance increases in single and multi-program workloads, respectively.