An Inexact Ultra-low Power Bio-signal Processing Architecture With Lightweight Error Recovery
| Autor: | David Atienza, Ruben Braojos, Giovanni Ansaloni, Laura Pozzi, Loris Duch, Soumya Basu |
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| Předmět: |
Signal processing
Correctness Computer science Reliability (computer networking) Distributed computing 020208 electrical & electronic engineering Inexact computing 02 engineering and technology Low-power architectural optimization 020202 computer hardware & architecture Hardware and Architecture Wireless Body Sensor Nodes 0202 electrical engineering electronic engineering information engineering Key (cryptography) Overhead (computing) Software Energy (signal processing) Degradation (telecommunications) Efficient energy use |
| Popis: | The energy efficiency of digital architectures is tightly linked to the voltage level (Vdd) at which they operate. Aggressive voltage scaling is therefore mandatory when ultra-low power processing is required. Nonetheless, the lowest admissible Vdd is often bounded by reliability concerns, especially since static and dynamic non-idealities are exacerbated in the near-threshold region, imposing costly guard-bands to guarantee correctness under worst-case conditions. A striking alternative, explored in this paper, waives the requirement for unconditional correctness, undergoing more relaxed constraints. First, after a run-time failure, processing correctly resumes at a later point in time. Second, failures induce a limited Quality-of-Service (QoS) degradation. We focus our investigation on the practical scenario of embedded bio-signal analysis, a domain in which energy efficiency is key, while applications are inherently error-tolerant to a certain degree. Targeting a domain-specific multi-core platform, we present a study of the impact of inexactness on application-visible errors. Then, we introduce a novel methodology to manage them, which requires minimal hardware resources and a negligible energy overhead. Experimental evidence show that, by tolerating 900 errors/hour, the resulting inexact platform can achieve an efficiency increase of up to 24%, with a QoS degradation of less than 3%. |
| Databáze: | OpenAIRE |
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