Abstract

It is expected that (single chip) multiprocessors will increasingly be deployed to realize high-performance embedded systems. Because in current technologies the dynamic power consumption dominates the static power dissipation, an effective technique to reduce energy consumption is to employ as many processors as possible in order to finish the tasks as early as possible, and to use the remaining time before the deadline (the slack) to apply voltage scaling. We refer to this heuristic as schedule and stretch (S&S). However, since the static power consumption is expected to become more significant, this approach is no longer efficient when leakage current is taken into account. In this paper, we first show for which combinations of leakage current, supply voltage, and clock frequency the static power consumption dominates the dynamic power dissipation. These results imply that, at a certain point, it is no longer advantageous from an energy perspective to employ as many processors as possible. Thereafter, a heuristic is presented to schedule the tasks on a number of processors that minimizes the total energy consumption. Experimental results obtained using a public task graph benchmark set show that our leakage-aware scheduling algorithm reduces the total energy consumption by up to 24% for tight deadlines (1.5/spl times/ the critical path length) and by up to 67% for loose deadlines (8/spl times/ the critical path length) compared to S&S.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.