Enhancing Power, Performance, and Energy Efficiency in Chip Multiprocessors Exploiting Inverse Thermal Dependence

Abstract

Technology scaling of complementary metal–oxide–semiconductor has resulted in new thermal behavior where increase in operating temperature results in reduced circuit propagation delay. This paper exploits this inverse thermal dependence (ITD) for power, performance, and temperature optimization in single-core and multicore processor architectures for various thermally hot and cold applications. Since ITD increases the maximum achievable operating frequency of a processor at high temperatures, it is used to reduce the execution time of applications. Dynamic thermal management (DTM) techniques, such as activity migration (AM), dynamic voltage frequency scaling (DVFS), and throttling, are modified to leverage ITD to either enhance the performance or the energy efficiency. While recent work observed the ITD effect for 45- and 32-nm technologies, in this paper, we explore future technologies through predictive SPICE models for 20-, 14-, 10-, and 7-nm technologies. The results show that the ITD-aware techniques reduce the execution time, energy-delay product (EDP) and energy-delay-square product by up to 28%, 33%, and 48%, respectively. Moreover, the ITD-aware DVFS yields the lowest execution time while resulting in the most uniform thermal profile and thus enhanced reliability. Overall, the ITD-aware techniques reduce the execution time and EDP, both in combination with DTM techniques or stand-alone, especially at lower than nominal operating voltages.