EVA: an efficient vision architecture for mobile systems

Authors:
Jason Clemons;Andrea Pellegrini;Silvio Savarese;Todd Austin
Affiliations:
University of Michigan, Ann Arbor, Michigan;University of Michigan, Ann Arbor, Michigan;University of Michigan, Ann Arbor, Michigan;University of Michigan, Ann Arbor, Michigan
Venue:
Proceedings of the 2013 International Conference on Compilers, Architectures and Synthesis for Embedded Systems
Year:
2013

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Abstract

The capabilities of mobile devices have been increasing at a momentous rate. As better processors have merged with capable cameras in mobile systems, the number of computer vision applications has grown rapidly. However, the computational and energy constraints of mobile devices have forced computer vision application developers to sacrifice accuracy for the sake of meeting timing demands. To increase the computational performance of mobile systems we present EVA. EVA is an application-specific heterogeneous multi-core having a mix of computationally powerful cores with energy efficient cores. Each core of EVA has computation and memory architectural enhancements tailored to the application traits of vision codes. Using a computer vision benchmarking suite, we evaluate the efficiency and performance of a wide range of EVA designs. We show that EVA can provide speedups of over 9x that of an embedded processor while reducing energy demands by as much as 3x.