Fair-Share Scheduling for Performance-Asymmetric Multicore Architecture via Scaled Virtual Runtime

As users begin to demand applications with superior user experience and high service quality, asymmetric multicore processors are increasingly adopted in embedded systems due to their architectural benefits in improved performance and power savings. While fair-share scheduling is a crucial kernel service for such applications, it is still in an early stage when it comes to performance-asymmetric multicore architecture. In this paper, we propose a new fair-share scheduler by adopting the notion of scaled CPU time which reflects performance asymmetry between different types of cores. Our scheduler can work with kernel's dynamic resource control mechanisms since it makes use of a varying performance ratio between cores and thus captures dynamic performance asymmetry such as a core's changing operating frequency. We develop our approach on top of ARM's big. LITTLE architecture which runs Linaro's scheduling framework. Since Linaro's relies on the completely fair scheduler(CFS) of the Linux kernel and CFS is virtual runtime based, we revise the notion of virtual runtime using the scaled CPU time and incorporate it into the proposed approach. As a result, our approach achieves fair-share scheduling by simply balancing tasks' virtual runtimes. To demonstrate its effectiveness, we have implemented the proposed scheduler and performed a series of experiments on ARM's Versatile Express TC2 board. We ran the SPEC CPU2006 and PARSEC benchmarks for three minutes and measured tasks' virtual runtimes. We observed that the maximum virtual runtime difference was only 0.69 seconds in our approach while the original CFS yielded the maximum difference of 8.35 seconds.