LD-DVS: load-aware dual-speed dynamic voltage scaling
by Christian Poellabauer, Dinesh Rajan, Russell Zuck
International Journal of Embedded Systems (IJES), Vol. 4, No. 2, 2009

Abstract: The goal of dynamic voltage scaling (DVS) is to maximise the energy savings while ensuring that applications' real-time requirements are met. Accurate predictions of task run-times are necessary to compute an appropriate CPU frequency that achieves high energy savings, avoids deadlines misses and reduces the overheads caused by frequent changes between different frequency levels. This paper experimentally explores an architecture based on the XScale PXA255 processor and shows that workload-awareness is not only required for accurate predictions of utilisation, but also that in systems with a discrete number of frequency levels, the energy savings achieved by existing dual-speed DVS approaches (where an optimal theoretical CPU speed is computed and then approximated by choosing the two neighbouring discrete speed levels) are suboptimal. As a consequence, this work introduces an online approach to dual-speed DVS that formulates a model for speed selection based on the workload characteristics of the current task set and computes a frequency pair that yields the best possible energy savings for a given task set and workload.

Online publication date: Thu, 20-Aug-2009

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Embedded Systems (IJES):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com