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An Ultra-Low-Power Application-Specific Processor for Compressed Sensing

In English

Författare

  • Jeremy Constantin
  • Ahmed Dogan
  • Oskar Andersson
  • Pascal Meinerzhagen
  • Joachim Rodrigues
  • David Atienza
  • Andreas Burg

Redaktör

  • Ayse Coskun
  • Andreas Burg
  • Ricardo Reis
  • Matthew Guthaus

Summary, in English

Compressed sensing (CS) is a universal low-complexity data compression technique for signals that have a sparse representation in some domain. While CS data compression can be done both in the analog- and digital domain, digital implementations are often used on low-power sensor nodes, where an ultra-low-power (ULP) processor carries out the algorithm on Nyquist-rate sampled data. In such systems an energy-efficient implementation of the CS compression kernel is a vital ingredient to maximize battery lifetime. In this paper, we propose an application-specific instruction-set processor (ASIP) processor that has been optimized for CS data compression and for operation in the subthreshold (sub-VT) regime. The design is equipped with specific sub-VT capable standard-cell based memories, to enable low-voltage operation with low leakage. Our results show that the proposed ASIP accomplishes 62× speed-up and 11.6× power savings with respect to a straightforward CS implementation running on the baseline low-power processor without instruction set extensions.

Publiceringsår

2013

Språk

Engelska

Sidor

88-106

Publikation/Tidskrift/Serie

IFIP Advances in Information and Communication Technology

Volym

418

Dokumenttyp

Del av eller Kapitel i bok

Förlag

Springer

Ämne

  • Electrical Engineering, Electronic Engineering, Information Engineering

Status

Published

ISBN/ISSN/Övrigt

  • ISBN: 978-3-642-45073-0
  • ISBN: 978-3-642-45072-3