Inexact-aware architecture design for ultra-low power bio-signal analysis

Soumya Basu, Pablo Garcia Del Valle, Georgios Karakonstantis, Giovanni Ansaloni, Laura Pozzi, David Atienza

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This study introduces an inexact, but ultra-low power, computing architecture devoted to the embedded analysis of bio-signals. The platform operates at extremely low voltage supply levels to minimise energy consumption. In this scenario, the reliability of static RAM (SRAM) memories cannot be guaranteed when using conventional 6-transistor implementations. While error correction codes and dedicated SRAM implementations can ensure correct operations in this near-threshold regime, they incur in significant area and energy overheads, and should therefore be employed judiciously. Herein, the authors propose a novel scheme to design inexact computing architectures that selectively protects memory regions based on their significance, i.e. their impact on the end-to-end quality of service, as dictated by the bio-signal application characteristics. The authors illustrate their scheme on an industrial benchmark application performing the power spectrum analysis of electrocardiograms. Experimental evidence showcases that a significance-based memory protection approach leads to a small degradation in the output quality with respect to an exact implementation, while resulting in substantial energy gains, both in the memory and the processing subsystem.
Original languageEnglish
Number of pages9
JournalIET Computers And Digital Techniques
Early online date20 Sep 2016
Publication statusEarly online date - 20 Sep 2016

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