μBrain: An Event-Driven and Fully Synthesizable Architecture for Spiking Neural Networks.

Frontiers in Neuroscience
Jan StuijtFederico Corradi

Abstract

The development of brain-inspired neuromorphic computing architectures as a paradigm for Artificial Intelligence (AI) at the edge is a candidate solution that can meet strict energy and cost reduction constraints in the Internet of Things (IoT) application areas. Toward this goal, we present μBrain: the first digital yet fully event-driven without clock architecture, with co-located memory and processing capability that exploits event-based processing to reduce an always-on system's overall energy consumption (μW dynamic operation). The chip area in a 40 nm Complementary Metal Oxide Semiconductor (CMOS) digital technology is 2.82 mm2 including pads (without pads 1.42 mm2). This small area footprint enables μBrain integration in re-trainable sensor ICs to perform various signal processing tasks, such as data preprocessing, dimensionality reduction, feature selection, and application-specific inference. We present an instantiation of the μBrain architecture in a 40 nm CMOS digital chip and demonstrate its efficiency in a radar-based gesture classification with a power consumption of 70 μW and energy consumption of 340 nJ per classification. As a digital architecture, μBrain is fully synthesizable and lends to a fast development-t...Continue Reading

References

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Sep 4, 2013·Nanotechnology·Giacomo IndiveriThemistoklis Prodromakis
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Dec 29, 2020·Nature Electronics·J GrollierM D Stiles

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Software Mentioned

Intel Movidius
Google EdgeTPU
Linux
Tensorflow
μBrain
MNIST

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