Performance-driven dynamic thermal management of MPSoC based on task rescheduling

Abstract

High level of integration has led to the advent of Multiprocessor System-on-Chip (MPSoC) which consists of multiple processor cores and accelerators on the same die. A MPSoC programming model is based on a task graph where tasks are assigned to cores to maximize performance. To address thermal hotspots in MPSoCs, coarse-grain power management techniques based on Dynamic Frequency Scaling (DFS) are widely used. DFS is reactive in nature and has detrimental effects on performance. We propose an alternative solution based on dynamic task rescheduling where a temperature prediction scheme is built into the scheduler. The temperature look-ahead scheme is used for task reassignment or delay insertion in scheduling. Since temperature prediction and task assignment are done at runtime, both must be simple and extremely fast. To that end, we propose a heuristic solution based on a limited branch-and-bound search and compare results against an optimal Integer Linear Programming (ILP)-based solution. The proposed approach is shown to be superior to frequency scaling, and the resulting schedule length is within 5% to 10% of the optimal solution as obtained from ILP formulation.