Title :
An Embedded Vision Engine (EVE) for automotive vision processing
Author :
Mandal, Dipan Kumar ; Sankaran, Jagadeesh ; Gupta, Arpan ; Castille, Kyle ; Gondkar, Shraddha ; Kamath, Sanmati ; Sundar, Pooja ; Phipps, Alan
Author_Institution :
Texas Instrum., Bangalore, India
Abstract :
This paper introduces Embedded Vision Engine (EVE) - a fully programmable, specialized vector processor architecture aimed at solving challenging Computer Vision applications encountered in Advanced Driver Assistance Systems (ADAS). The paper outlines the complexity of automotive vision applications, establishes why specialized architecture (like EVE) is needed and outlines the EVE architecture, its components and programming model. We present comparative benchmarks and provide an overview of many carefully crafted features of EVE for power management, inter processor communication, functional safety and software debug that helps in building a scalable, area-power efficient System-on-Chip (SoC) solutions for the cost, power and safety sensitive automotive vision space.
Keywords :
computer vision; system-on-chip; traffic engineering computing; ADAS; EVE architecture; advanced driver assistance system; area-power efficient SoC; automotive vision processing; computer vision; embedded vision engine; functional safety; interprocessor communication; power management; software debug; system-on-chip; vector processor architecture; Automotive engineering; Buffer storage; Computer architecture; Digital signal processing; Engines; Safety; Vectors; ADAS; Automotive Vision; Computer Vision; Processor Architecture; SIMD processor; Vector Processor;
Conference_Titel :
Circuits and Systems (ISCAS), 2014 IEEE International Symposium on
Conference_Location :
Melbourne VIC
Print_ISBN :
978-1-4799-3431-7
DOI :
10.1109/ISCAS.2014.6865062
