Exploring spiking neural networks (SNN) for low Size, Weight, and Power (SWaP) benefits
Bihl, Trevor J. and Farr, Patrick and Di Caterina, Gaetano and Kirkland, Paul and Vicente Sola, Alex and Manna, Davide and Liu, Jundong and Combs, Kara; Bui, Tung X., ed. (2024) Exploring spiking neural networks (SNN) for low Size, Weight, and Power (SWaP) benefits. In: Proceedings of the 57th Annual Hawaii International Conference on System Sciences, HICSS 2024. Proceedings of the Annual Hawaii International Conference on System Sciences . Shidler College of Business, University of Hawaii at Manoa, USA, pp. 7561-7570. ISBN 9780998133171 (https://hdl.handle.net/10125/107294)
Preview |
Text.
Filename: Bihl-etal-HICSS-2024-Exploring-spiking-neural-networks-for-low-Size-Weight-and-Power-benefits.pdf
Final Published Version License: Download (641kB)| Preview |
Abstract
Size, Weight, and Power (SWaP) concerns are growing as artificial intelligence (AI) use spreads in edge applications. AI algorithms, such as artificial neural networks (ANNs), have revolutionized many fields, e.g. computer vision (CV), but at a large computational/power burden. Biological intelligence is notably more computationally efficient. Neuromorphic edge processors and spiking neural networks (SNNs) aim to follow biology closer with spike-based operations resulting in sparsity and lower-SWaP operations than traditional ANNs with SNNs only “firing/spiking” when needed. Understanding the trade space of SWaP when embracing neuromorphic computing has not been studied heavily. To addresses this, we present a repeatable and scalable apples-to-apples comparison of traditional ANNs and SNNs for edge processing with demonstration on both classical and neuromorphic edge hardware. Results show that SNNs combined with neuromorphic hardware can provide comparable accuracy for CV to ANNs at 1/10th the power.
ORCID iDs
Bihl, Trevor J., Farr, Patrick, Di Caterina, Gaetano ORCID: https://orcid.org/0000-0002-7256-0897, Kirkland, Paul ORCID: https://orcid.org/0000-0001-5905-6816, Vicente Sola, Alex ORCID: https://orcid.org/0000-0002-2370-6562, Manna, Davide ORCID: https://orcid.org/0000-0001-8963-5050, Liu, Jundong and Combs, Kara; Bui, Tung X.-
-
Item type: Book Section ID code: 87399 Dates: DateEvent3 January 2024Published12 September 2023AcceptedNotes: This paper was published in the proceedings of the 57th Hawaii International Conference on System Sciences (HICSS), 2024, pp. 7561-7570 Subjects: Science > Mathematics > Electronic computers. Computer science Department: Faculty of Engineering > Electronic and Electrical Engineering Depositing user: Pure Administrator Date deposited: 21 Nov 2023 13:00 Last modified: 11 Nov 2024 15:33 URI: https://strathprints.strath.ac.uk/id/eprint/87399