Adapt

Abstract

Since multicore systems offer greater performance via parallelism, future computing is progressing towards use of multicore machines with large number of cores. However, the performance of emerging multithreaded programs often does not scale to fully utilize the available cores. Therefore, simultaneously running multiple multithreaded applications becomes inevitable to fully exploit the computing potential of such machines. However, maximizing the performance and throughput on multicore machines in the presence of multiple multithreaded programs is a challenge for the OS. We have observed that the state-of-the-art contention management algorithms fail to effectively coschedule multithreaded programs on multicore machines. To address the above challenge, we present ADAPT, a scheduling framework that continuously monitors the resource usage of multithreaded programs and adaptively coschedules them such that they interfere with each other's performance as little as possible. In addition, ADAPT selects appropriate memory allocation and scheduling policies according to the workload characteristics. We have implemented ADAPT on a 64-core Supermicro server running Solaris 11 and evaluated it using 26 multithreaded programs including the TATP database application, SPECjbb2005, and programs from Phoenix, PARSEC, and SPEC OMP suites. The experimental results show that ADAPT substantially improves total turnaround time and system utilization relative to the default Solaris 11 scheduler.

Tumbler

“…It eliminates scheduler-related interference between concurrent jobs and improves performance in coscheduled runs. ADAPT [Pusukuri et al 2013] coschedules multithreaded applications by using machine-learning techniques to characterize the interference between multithreaded applications. However, none of these works consider the load imbalance problem in multi-CPU multicore systems addressed in this work.…”