Efficient Video and Audio processing with Loihi 2

Loihi 2 is an asynchronous, brain-inspired research processor that generalizes several fundamental elements of neuromorphic architecture, such as stateful neuron models communicating with event-driven spikes, in order to address limitations of the first generation Loihi. Here we explore and characte...

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Bibliographic Details
Main Authors Shrestha, Sumit Bam, Timcheck, Jonathan, Frady, Paxon, Campos-Macias, Leobardo, Davies, Mike
Format Journal Article
LanguageEnglish
Published 04.10.2023
Subjects
Computer Science - Emerging Technologies
Computer Science - Neural and Evolutionary Computing
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Summary:Loihi 2 is an asynchronous, brain-inspired research processor that generalizes several fundamental elements of neuromorphic architecture, such as stateful neuron models communicating with event-driven spikes, in order to address limitations of the first generation Loihi. Here we explore and characterize some of these generalizations, such as sigma-delta encapsulation, resonate-and-fire neurons, and integer-valued spikes, as applied to standard video, audio, and signal processing tasks. We find that these new neuromorphic approaches can provide orders of magnitude gains in combined efficiency and latency (energy-delay-product) for feed-forward and convolutional neural networks applied to video, audio denoising, and spectral transforms compared to state-of-the-art solutions.
DOI:10.48550/arxiv.2310.03251