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Mapping Adaptive Particle Filters to Heterogeneous Reconfigurable Systems

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Published:29 December 2014Publication History
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Abstract

This article presents an approach for mapping real-time applications based on particle filters (PFs) to heterogeneous reconfigurable systems, which typically consist of multiple FPGAs and CPUs. A method is proposed to adapt the number of particles dynamically and to utilise runtime reconfigurability of FPGAs for reduced power and energy consumption. A data compression scheme is employed to reduce communication overhead between FPGAs and CPUs. A mobile robot localisation and tracking application is developed to illustrate our approach. Experimental results show that the proposed adaptive PF can reduce up to 99% of computation time. Using runtime reconfiguration, we achieve a 25% to 34% reduction in idle power. A 1U system with four FPGAs is up to 169 times faster than a single-core CPU and 41 times faster than a 1U CPU server with 12 cores. It is also estimated to be 3 times faster than a system with four GPUs.

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  1. Mapping Adaptive Particle Filters to Heterogeneous Reconfigurable Systems

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        • Published in

          cover image ACM Transactions on Reconfigurable Technology and Systems
          ACM Transactions on Reconfigurable Technology and Systems  Volume 7, Issue 4
          January 2015
          213 pages
          ISSN:1936-7406
          EISSN:1936-7414
          DOI:10.1145/2699137
          • Editor:
          • Steve Wilton
          Issue’s Table of Contents

          Copyright © 2014 ACM

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 29 December 2014
          • Accepted: 1 March 2014
          • Revised: 1 February 2014
          • Received: 1 June 2013
          Published in trets Volume 7, Issue 4

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