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Low-cost and hardware-efficient design of trigonometric functions is challenging. Stochastic computing (SC), an emerging computing model processing random bit-streams, offers promising solutions for this problem. The existing implementations, however, often overlook the importance of the data converters necessary to generate the needed bit-streams. While recent advancements in SC bit-stream generators focus on basic arithmetic operations such as multiplication and addition, energy-efficient SC design of non-linear functions demands attention to both the computation circuit and the bit-stream generator. This work introduces TriSC, a novel approach for SC-based design of trigonometric functions enjoying state-of-the-art (SOTA) quasi-random bit-streams. Unlike SOTA SC designs of trigonometric functions that heavily rely on delay elements to decorrelate bit-streams, our approach avoids delay elements while improving the accuracy of the results. TriSC yields significant energy savings of up to 92% compared to SOTA. As two novel use cases studied for the first time in SC literature, we employ the proposed design for 2D image transformation and forward kinematics of a robotic arm, two computation-intensive applications demanding low-cost trigonometric designs.
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Benefits of Stochastic Computing in Hearing Aid Filterbank Design
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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- Award ID(s):
- 2006704
- PAR ID:
- 10324341
- Date Published:
- Journal Name:
- 2021 IEEE Biomedical Circuits and Systems Conference (BioCAS)
- ISSN:
- 2766-4465
- Page Range / eLocation ID:
- 1-5
- Format(s):
- Medium: X
- 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/11109/BioCAS49922.2021.9645021
