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Issue No. 12 - December (2003 vol. 36)
ISSN: 0018-9162
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>

M. C. Huang et al., "Dynamically Tuning Processor Resources with Adaptive Processing," in Computer, vol. 36, no. , pp. 49-58, 2003.
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