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/spl trade/) 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.


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    Titel :

    RSVP/spl trade/: an automotive vector processor


    Beteiligte:
    Chiricescu, S. (Autor:in) / Schuette, M. (Autor:in) / Essick, R. (Autor:in) / Lucas, B. (Autor:in) / May, P. (Autor:in) / Moat, K. (Autor:in) / Norris, J. (Autor:in)


    Erscheinungsdatum :

    01.01.2004


    Format / Umfang :

    547361 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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