NDLI: EVE: A Flexible SIMD Coprocessor for Embedded Vision Applications

Content Provider	Springer Nature Link
Author	Sankaran, Jagadeesh Hung, Ching Yu Kisačanin, Branislav
Copyright Year	2013
Abstract	In this paper we introduce EVE (embedded vision/vector engine), with a FlexSIMD (flexible SIMD) architecture highly optimized for embedded vision. We show how EVE can be used to meet the growing requirements of embedded vision applications in a power- and area-efficient manner. EVE’s SIMD features allow it to accelerate low-level vision functions (such as image filtering, color-space conversion, pyramids, and gradients). With added flexibility of data accesses, EVE can also be used to accelerate many mid-level vision tasks (such as connected components, integral image, histogram, and Hough transform). Our experiments with a silicon implementation of EVE show that it performs many low- and mid-level vision functions with a 3–12x speed advantage over a C64x+DSP, while consuming less power and area. EVE also achieves code size savings of 4–6x over a C64x+DSP for regular loops. Thanks to its flexibility and programmability, we were able to implement two end-to-end vision applications on EVE and achieve more than a 5× application-level speedup over a C64x+. Having EVE as a coprocessor next to a DSP or a general purpose processor, algorithm developers have an option to accelerate the low- and mid-level vision functions on EVE. This gives them more room to innovate and use the DSP for new, more complex, high-level vision algorithms.
Starting Page	95
Ending Page	107
Page Count	13
File Format	PDF
ISSN	19398018
Journal	Journal of Signal Processing Systems
Volume Number	75
Issue Number	2
e-ISSN	19398115
Language	English
Publisher	Springer US
Publisher Date	2013-07-10
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Embedded vision Coprocessor Architecture DSP EVE SIMD Flexible SIMD FlexSIMD VLIW Signal, Image and Speech Processing Circuits and Systems Electrical Engineering Image Processing and Computer Vision Pattern Recognition Computer Imaging, Vision, Pattern Recognition and Graphics
Content Type	Text
Resource Type	Article
Subject	Theoretical Computer Science Signal Processing Control and Systems Engineering Information Systems Modeling and Simulation Hardware and Architecture

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