Proactive task migration with a self-adjusting migration threshold for dynamic thermal management of multi-core processors

Request for more computation power steadily forces designers to provide more powerful processors using more number of cores on a single chip. The increasing complexity of processors leads to higher integration density, power density, and temperature. For avoiding thermal emergencies, various dynamic thermal management techniques have been presented. In this paper, we present a novel online self-adjusting temperature threshold schema for dynamic thermal management to minimize both average and peak temperature with very low performance overhead. Our proposed algorithm adjusts migration threshold according to workload and hardware platforms. The experimental results indicate that our technique can significantly decrease the average and peak temperature compared to Linux standard scheduler, and two well-known thermal management techniques: PDTM and TAS.