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Energy optimal speed control of a producer--consumer device pair
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ACM Transactions on Embedded Computing Systems (TECS) archive
Volume 6 ,  Issue 4  (September 2007) table of contents
Special Section LCTES'05
Article No. 30  
Year of Publication: 2007
ISSN:1539-9087
Authors
Ravishankar Rao  Arizona State University, Tempe, Arizona
Sarma Vrudhula  Arizona State University, Tempe, Arizona
Publisher
ACM  New York, NY, USA
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ABSTRACT

We propose a modular approach for minimizing the total energy consumed by a pair of generic communicating devices (producer--consumer scenario) by jointly controlling their speed profiles. Each device (like a CPU, or disk drive) is assumed to have a controllable variable called its speed (e.g., a CPU's clock frequency, a disk drive's spindle motor speed) that affects its power consumption and performance (e.g., throughput, data transfer rate). The device and task models we analyzed were inspired by applications like CD recording (hard drive to CD drive data transfer) and data processing (disk drive to CPU data transfer). The proposed solution can be used for any pair of devices with convex (for continuous speed sets) or W-convex (a discrete version of a convex function for discrete speed sets) power--speed relationships. For discrete speed sets, the method operates directly on the power--speed values and does not require an analytical relationship between power and speed. The key to solving the two-device optimization problem was the observation that it could be split into two single device parametric optimization problems, where the parameters correspond to the common task that both the devices must execute. The following divide-and-conquer approach is proposed: [divide] the optimal speed policy and energy consumption of each device is derived as an analytical function of its task parameters; [conquer] the optimal values of these parameters are found by minimizing the sum of the parameterized energy functions and plugged back into the parameterized speed profiles. The main advantage of this approach is that each device can be characterized independently and this allows system designers to mix and match manufacturer-supplied device energy curves to evaluate and optimize different application scenarios. We demonstrate our approach using three device characterization examples (for a CD drive, hard drive, and a CPU) and two application scenarios (CD recording, MD5 checksum computation).


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Ravishankar Rao: colleagues
Sarma Vrudhula: colleagues