[2309.03221] SPAIC: A sub-$μ$W/Channel, 16-Channel General-Purpose Event-Based Analog Front-End with Dual-Mode Encoders
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Computer Science > Hardware Architecture

arXiv:2309.03221 (cs)
[Submitted on 31 Aug 2023]

Title:SPAIC: A sub-$μ$W/Channel, 16-Channel General-Purpose Event-Based Analog Front-End with Dual-Mode Encoders

Authors:Shyam Narayanan, Matteo Cartiglia, Arianna Rubino, Charles Lego, Charlotte Frenkel, Giacomo Indiveri
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Abstract:Low-power event-based analog front-ends (AFE) are a crucial component required to build efficient end-to-end neuromorphic processing systems for edge computing. Although several neuromorphic chips have been developed for implementing spiking neural networks (SNNs) and solving a wide range of sensory processing tasks, there are only a few general-purpose analog front-end devices that can be used to convert analog sensory signals into spikes and interfaced to neuromorphic processors. In this work, we present a novel, highly configurable analog front-end chip, denoted as SPAIC (signal-to-spike converter for analog AI computation), that offers a general-purpose dual-mode analog signal-to-spike encoding with delta modulation and pulse frequency modulation, with tunable frequency bands. The ASIC is designed in a 180 nm process. It supports and encodes a wide variety of signals spanning 4 orders of magnitude in frequency, and provides an event-based output that is compatible with existing neuromorphic processors. We validated the ASIC for its functions and present initial silicon measurement results characterizing the basic building blocks of the chip.
Comments: 5 pages, 10 figures, Accepted for lecture at IEEE BioCAS Conference 2023
Subjects: Hardware Architecture (cs.AR); Emerging Technologies (cs.ET); Neural and Evolutionary Computing (cs.NE)
Cite as: arXiv:2309.03221 [cs.AR]
  (or arXiv:2309.03221v1 [cs.AR] for this version)
  https://doi.org/10.48550/arXiv.2309.03221

Submission history

From: Shyam Narayanan [view email]
[v1] Thu, 31 Aug 2023 19:53:04 UTC (24,023 KB)
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