Task Migration for Dynamic Power and Performance Characteristics on Many-Core Distributed Operating Systems

Abstract

Spatial locality of task execution will become more important on future hardware platforms since the number of cores are steadily increasing. The large amount of cores requires more intelligent power management due to the notion of spatial locality, and the high chip density requires an increased thermal awareness in order to avoid thermal hotspots on the chip. At the same time, high performance of the CPU is only achieved by parallelizing tasks over the chip in order to fully utilize the hardware. This paper presents a task migration mechanism for distributed operating systems running on many-core platforms. In this work, we evaluate the performance and energy efficiency of an implemented task migration mechanism. This is shown by parallelizing tasks as the performance of a single core is not sufficient, and by collecting tasks to as few cores as possible as CPU load is low. The task migration mechanism is implemented as a library for FreeRTOS using 1300 lines of code, and introduced a total task migration overhead of 100 ms on a shared memory platform. With the presented task migration mechanism, we intend to improve the dynamism of power and performance characteristics in distributed many-core operating systems.