EFFEX: an embedded processor for computer vision based feature extraction

Authors:
Jason Clemons;Andrew Jones;Robert Perricone;Silvio Savarese;Todd Austin
Affiliations:
University of Michigan, Ann Arbor, MI;University of Michigan, Ann Arbor, MI;University of Michigan, Ann Arbor, MI;University of Michigan, Ann Arbor, MI;University of Michigan, Ann Arbor, MI
Venue:
Proceedings of the 48th Design Automation Conference
Year:
2011

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Abstract

The deployment of computer vision algorithms in mobile applications is growing at a rapid pace. A primary component of the computer vision software pipeline is feature extraction, which identifies and encodes relevant image features. We present an embedded heterogeneous multicore design named EFFEX that incorporates novel functional units and memory architecture support, making it capable of increasing mobile vision performance while balancing power and area. We demonstrate this architecture running three common feature extraction algorithms, and show that it is capable of providing significant speedups at low cost. Our simulations show a speedup of as much as 14x for feature extraction with a decrease in energy of 40x for memory accesses.