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Issue No.12 - December (2003 vol.36)
pp: 49-58
David H. Albonesi , University of Rochester
Rajeev Balasubramonian , University of Rochester
Steven G. Dropsho , University of Rochester
Sandhya Dwarkadas , University of Rochester
Eby G. Friedman , University of Rochester
Michael C. Huang , University of Rochester
Volkan Kursun , University of Rochester
Grigorios Magklis , University of Rochester
Michael L. Scott , University of Rochester
Greg Semeraro , University of Rochester
Pradip Bose , IBM T.J. Watson Research Center
Alper Buyuktosunoglu , IBM T.J. Watson Research Center
Peter W. Cook , IBM T.J. Watson Research Center
Stanley E. Schuster , IBM T.J. Watson Research Center
<p>The <em>adaptive processing approach</em> improves microprocessor energy efficiency by dynamically tuning major resources during execution to better match varying application needs. This tuning usually involves reducing a resource's size when its full capabilities are not needed, then restoring the disabled portions when they are needed again.</p><p>Adaptive processors require few additional transistors. Further, because adaptation occurs only in response to infrequent trigger events, the decision logic can be placed into a low-leakage state until such events occur.</p>
David H. Albonesi, Rajeev Balasubramonian, Steven G. Dropsho, Sandhya Dwarkadas, Eby G. Friedman, Michael C. Huang, Volkan Kursun, Grigorios Magklis, Michael L. Scott, Greg Semeraro, Pradip Bose, Alper Buyuktosunoglu, Peter W. Cook, Stanley E. Schuster, "Dynamically Tuning Processor Resources with Adaptive Processing", Computer, vol.36, no. 12, pp. 49-58, December 2003, doi:10.1109/MC.2003.1250883
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