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

TL;DR

This paper introduces SPAIC, a highly configurable, low-power 16-channel analog front-end chip that converts diverse analog signals into spikes using dual-mode encoding, suitable for neuromorphic edge computing.

Contribution

The work presents a novel, general-purpose analog front-end chip with dual-mode encoding, supporting a wide frequency range and interfacing with neuromorphic processors, designed in 180 nm process.

Findings

Supports signals spanning 4 orders of magnitude in frequency

Provides event-based output compatible with neuromorphic processors

Initial silicon measurements validate core functionalities

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.