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

• Main Authors: Narayanan, Shyam, Cartiglia, Matteo, Rubino, Arianna, Lego, Charles, Frenkel, Charlotte, Indiveri, Giacomo
• Format: Journal Article
• Language: English
• Published: 31.08.2023
• Subjects: Computer Science - Emerging Technologies; Computer Science - Hardware Architecture; Computer Science - Neural and Evolutionary Computing
• DOI: 10.48550/arxiv.2309.03221

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.