Contention aware execution

Cross-core application interference due to contention for shared on-chip and off-chip resources pose a significant challenge to providing application level quality of service (QoS) guarantees on commodity multicore micro-architectures. Unexpected cross-core interference is especially problematic when considering latency-sensitive applications that are present in the web service data center application domains, such as web-search. The commonly used solution is to simply disallow the co-location of latency-sensitive applications and throughput-oriented batch applications on a single chip, leaving much of the processing capabilities of multicore micro-architectures underutilized. In this work we present a Contention Aware Execution Runtime (CAER) environment that provides a lightweight runtime solution that minimizes cross-core interference due to contention, while maximizing utilization. CAER leverages the ubiquitous performance monitoring capabilities present in current multicore processors to infer and respond to contention and requires no added hardware support. We present the design and implementation of the CAER environment, two separate contention detection heuristics, and approaches to respond to contention online. We evaluate our solution using the SPEC2006 benchmark suite. Our experiments show that when allowing co-location with CAER, as opposed to disallowing co-location, we are able to increase the utilization of the multicore CPU by 58% on average. Meanwhile CAER brings the overhead due to allowing co-location from 17% down to just 4% on average.