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Adaptive Parallelism Exploitation under Physical and Real-Time Constraints for Resilient Systems

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Published:03 September 2014Publication History
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Abstract

This article introduces the resilient adaptive algebraic architecture that aims at adapting parallelism exploitation of a matrix multiplication algorithm in a time-deterministic fashion to reduce power consumption while meeting real-time deadlines present in most DSP-like applications. The proposed architecture provides low-overhead error correction capabilities relying on the hardware implementation of the algorithm-based fault-tolerance method that is executed concurrently with matrix multiplication, providing efficient occupation of memory and power resources. The Resilient Adaptive Algebraic Architecture (RA3) is evaluated using three real-time industrial case studies from the telecom and multimedia application domains to present the design space exploration and the adaptation possibilities the architecture offers to hardware designers. RA3 is compared in its performance and energy efficiency with standard high-performance architectures, namely a GPU and an out-of-order general-purpose processor. Finally, we present the results of fault injection campaigns in order to measure the architecture resilience to soft errors.

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  1. Adaptive Parallelism Exploitation under Physical and Real-Time Constraints for Resilient 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 3
          Special Issue on 11th International Conference on Field-Programmable Technology (FPT'12) and Special Issue on the 7th International Workshop on Reconfigurable Communication-Centric Systems-on-Chip (ReCoSoC'12)
          August 2014
          199 pages
          ISSN:1936-7406
          EISSN:1936-7414
          DOI:10.1145/2664590
          Issue’s Table of Contents

          Copyright © 2014 ACM

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 3 September 2014
          • Accepted: 1 October 2013
          • Revised: 1 September 2013
          • Received: 1 January 2013
          Published in trets Volume 7, Issue 3

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