DocumentCode
3465679
Title
RSVP™: an automotive vector processor
Author
Chiricescu, S. ; Schuette, M. ; Essick, R. ; Lucas, B. ; May, P. ; Moat, K. ; Norris, J.
Author_Institution
Motorola Labs, Motorola Inc., Schaumburg, IL, USA
fYear
2004
fDate
14-17 June 2004
Firstpage
200
Lastpage
205
Abstract
A myriad of sensors (i.e., video, radar, laser, ultrasound, etc.) continuously monitoring the environment are incorporated in future automobiles. The algorithms processing the data captured by these sensors are streaming in nature and require high levels of processing power. Due to the characteristics of the automotive market, this processing power has to be delivered under very low energy and cost budgets. The Reconfigurable Streaming Vector Processing (RSVP™) is a vector coprocessor architecture which accelerates streaming data processing. This paper presents the RSVP architecture, programming model, and a first implementation. Our results show significant speedups on data streaming functions. Running compiled code, RSVP outperforms an ARM9 host processor on average by a factor of 31 on a set of kernels. From a performance/$ and performance/mW perspective, RSVP compares favorably with leading DSP architectures. The time to market is substantially reduced due to ease of programmability, elimination of hand-tuned assembly code, and support for software re-use through binary compatibility across multiple implementations.
Keywords
automobiles; automotive engineering; digital signal processing chips; reconfigurable architectures; time to market; traffic engineering computing; ARM9 host processor; DSP architectures; algorithms processing; automobiles; automotive market; automotive vector processor; cost budgets; data streaming functions; environment monitoring; hand tuned assembly code elimination; programming model; reconfigurable streaming vector processing architecture; sensors; streaming data processing; vector coprocessor architecture; Automobiles; Automotive engineering; Coprocessors; Costs; Laser radar; Monitoring; Sensor phenomena and characterization; Streaming media; Ultrasonic imaging; Vector processors;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Vehicles Symposium, 2004 IEEE
Print_ISBN
0-7803-8310-9
Type
conf
DOI
10.1109/IVS.2004.1336381
Filename
1336381
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