Optimizing Intratask Voltage Scheduling Using Profile and Data-Flow Information

Dongkun Shin, Jihong Kim

Abstract: Intratask dynamic-voltage scheduling (IntraDVS), which adjusts the supply voltage within an individual-task boundary, has been introduced as an effective technique for developing low-power single-task applications or low-power multitask applications, where a small number of tasks are dominant in total execution time. The original IntraDVS technique used the remaining worst case execution cycles, and the control-flow information to identify the voltage-scaling points (VSPs) of a program. In this paper, two kinds of improvement techniques enhancing the energy performance of the IntraDVS are proposed. One is to use profile information to optimize the voltage schedule for the remaining average-case execution path (RAEP-IntraDVS). The other is to use data-flow information to optimize the locations of VSPs [look-ahead IntraDVS (LaIntraDVS)]. The experimental results show that the RAEP-IntraDVS can reduce the energy consumption by 20% on average and the LaIntraDVS can reduce the energy consumption by 40%-45% compared with the original IntraDVS