Characterizing Processors for Time and Energy Optimization

Abstract

Energy and performance are important aspects of microprocessors and their verification and management require, measurement, estimation and analysis and these aspects are discussed through this research. A processor executes a computing job in a certain number of clock cycles. The clock frequency determines the time that the job will take. Another parameter, cycle efficiency or cycles per joule, determines how much energy the job will consume. The execution time measures performance and, in combination with energy dissipation, influences power, thermal behavior, power supply noise and battery life. We describe a method for power management of a processor. To show optimization of time and energy, we study several Intel processors from 45 nm, 32 nm and 22 nm technology nodes for both thermal design power (TDP) and peak power. They are characterized for two different predictive technology models: Bulk CMOS and High-K Metal Gate, which are available for analysis in H-spice simulation. Our analysis establishes correlation between the simulation data for an adder circuit and the processor data sheet, and then estimates operating frequency and cycle efficiency as functions of the supply voltage. This data is useful in managing the operational characteristics of processors, especially those used in mobile or remote systems where both execution time and energy are important. We illustrate how this information is utilized in managing the highest performance including turbo (over-clocking), lowest energy, and all in-between operating modes.