Computer Science University of Rochester Rochester / /
IndustryTerm
energy optimization / energy improvement / software pipelining / synchronous processor / cono sumes energy / on-line control algorithm / offline algorithm / then energy improvements / potential energy savings / overall energy savings / energy impact / real-time deadlines / energy improvements / Energy benefit / server systems / domain memory domain total energy reduction baseline machine / energy saving technique / energy savings / separate energy / on-line method / energy / off-line control algorithm / benchmark applications / energy zx9 / adaptive hardware / source-to-source locality-based fusion algorithm / energy consumption / program energy / off-line algorithm / energy cost / minimal energy / conventional superscalar processor / processor energy consumption / adaptive processors / on-line algorithm / energy efficiency / energy-efficient task scheduling / simplified energy model / aimed at saving energy / /
Organization
National Science Foundation / Computer Science University of Rochester Rochester / New York / /
The Energy Impact of Aggressive Loop Fusion YongKang Zhu, Grigorios Magklis, Michael L. Scott, Chen Ding, and David H. Albonesi Departments of Electrical and Computer Engineering and of Computer Science University of Roc