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.
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Constantin, J. et al. (2013). An Ultra-Low-Power Application-Specific Processor with Sub-VT Memories for Compressed Sensing. In: Burg, A., Coṣkun, A., Guthaus, M., Katkoori, S., Reis, R. (eds) VLSI-SoC: From Algorithms to Circuits and System-on-Chip Design. VLSI-SoC 2012. IFIP Advances in Information and Communication Technology, vol 418. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-45073-0_5
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DOI: https://doi.org/10.1007/978-3-642-45073-0_5
Publisher Name: Springer, Berlin, Heidelberg
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