Adaptive Processing: Dynamically Tuning Processor Resources for Energy Efficiency

The productivity of modern society has become inextricably linked to its ability to produce energy-efficient computing technology. Increasingly sophisticated mobile computing systems, powered for hours solely by batteries, continue to rapidly proliferate throughout society, while battery technology improves at a comparably slow pace. In large data centers, handling for example online orders for a .com company or sophisticated web searches, row upon row of tightly packed racks of computers may be warehoused in a city block. Microprocessor energy wastage in such a facility directly translates into higher electricity bills, and even getting sufficient electric supply from utilities to power such a center is no longer a given. Given this situation, energy efficiency has rapidly ascended to the forefront of modern microprocessor design.

By: David Albonesi, Rajeev Balasubramonian, Steven Dropsho, Sandhya Dwarkadas, Eby Friedman, Michael Huang, Volkan Kursun, Grigorios Magklis, Michael Scott, Greg Semeraro, Pradip Bose, Alper Buyuktosunoglu, Peter W. Cook, Stanley E. Schuster

Published in: RC22856 in 2003


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