Package-Aware Scheduling of embedded workloads for temperature and Energy management on heterogeneous MPSoCs

Abstract

In this paper, we present PASTEMP, a solution for Package Aware Scheduling for Thermal and Energy management using Multi- Parametric programming in heterogeneous embedded multiprocessor SoCs (MPSoCs). Based on the current thermal state of the system and current performance requirements of the workload, PASTEMP finds thermally safe and energy efficient voltage/frequency configurations for the cores on a MPSoC. The tasks are assigned to the cores depending on their performance demand and the current voltage/frequency of the core. The voltage/frequency settings of the cores are chosen through an optimization process which is based on the instantaneous thermal model we introduce to decouple the effect of package temperature from the temperature changes caused by the power consumption of the cores. To be able to find the best voltage/frequency settings at runtime, we use multi-parametric programming to separate the optimization into offline and online phases. According to our experimental results, compared to similar DTM techniques, PASTEMP results in up to 23% energy saving and 26% throughput improvement and reduces the deadline misses to more than a half while meeting all thermal constraints.