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Designing low-cost filterbanks is important due to severe resource limitations imposed by hearing aid size. Here, we develop a novel FIR filterbank employing stochastic computing (SC). SC-based filters use (pseudo)-random bitstreams to efficiently perform the core filtering operation. We demonstrate that SC is well-suited to low-cost filterbank design and compare our SC filterbank to a conventional sequential binary (SB) design. We show that the SC design achieves the same accuracy and latency as the SB one, with an exceptionally large 70% reduction in chip area. The power consumption of our proposed SC filterbank is 38-96% that of the SB design.
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Performance and Error Tolerance of Stochastic Computing-Based Digital Filter Design
Abstract— Recent advances in near-sensor computing have prompted the need to design low-cost digital filters for edge devices. Stochastic computing (SC), leveraging its probabilistic bit-streams, has emerged as a compelling alternative to traditional deterministic computing for filter design. This paper examines error tolerance, area and power efficiency, and accuracy loss in SC-based digital filters. Specifically, we investigate the impact of various stochastic number generators and increased filter complexity on both FIR and IIR filters. Our results indicate that in an error-free environment, SC exhibits a 49% area advantage and a 64% power efficiency improvement, albeit with a slight loss of accuracy, compared to traditional binary implementations. Furthermore, when the input bitstreams are subject to a 2% bit-flip error rate, SC FIR and SC IIR filters have a much smaller performance degradation (1.3X and 1.9X, respectively) than comparable binary filters. In summary, this work provides useful insights into the advantages of stochastic computing in digital filter design, showcasing its robust error resilience, significant area and power efficiency gains, and trade-offs in accuracy compared to traditional binary approaches.
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- Award ID(s):
- 2006704
- PAR ID:
- 10518946
- Publisher / Repository:
- IEEE
- Date Published:
- ISBN:
- 979-8-3503-5934-3
- Page Range / eLocation ID:
- 7 to 12
- Format(s):
- Medium: X
- Location:
- Kielce, Poland
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/DDECS60919.2024.10508903
