An ultra-low-power application-specific processor with sub-VT memories for compressed sensing

Constantin J, Dogan A, Andersson O, Meinerzhagen P, Rodrigues J, Atienza D, Burg A (2013)

Publication Type: Conference contribution

Publication year: 2013

Journal

IFIP Advances in Information and Communication Technology Springer Verlag

Publisher: Springer New York LLC

Book Volume: 418

Pages Range: 88-106

Conference Proceedings Title: IFIP Advances in Information and Communication Technology

Event location: USA

ISBN: 9783642450723

DOI: 10.1007/978-3-642-45073-0_5

Abstract

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.

Involved external institutions

École Polytechnique Fédérale de Lausanne (EPFL)

Switzerland (CH) Lund University / Lunds universitet

Sweden (SE)

How to cite

APA:

Constantin, J., Dogan, A., Andersson, O., Meinerzhagen, P., Rodrigues, J., Atienza, D., & Burg, A. (2013). An ultra-low-power application-specific processor with sub-VT memories for compressed sensing. In Matthew R. Guthaus, Srinivas Katkoori, Ayse Coskun, Andreas Burg, Srinivas Katkoori, Ricardo Reis, Ricardo Reis, Andreas Burg, Ayse Coskun, Matthew Guthaus (Eds.), IFIP Advances in Information and Communication Technology (pp. 88-106). USA: Springer New York LLC.

MLA:

Constantin, Jeremy, et al. "An ultra-low-power application-specific processor with sub-VT memories for compressed sensing." Proceedings of the 20th IFIP/IEEE International Conference on Very Large Scale Integration, VLSI-SoC 2012, USA Ed. Matthew R. Guthaus, Srinivas Katkoori, Ayse Coskun, Andreas Burg, Srinivas Katkoori, Ricardo Reis, Ricardo Reis, Andreas Burg, Ayse Coskun, Matthew Guthaus, Springer New York LLC, 2013. 88-106.

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