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Innatera’s Spiking Neural Processor

April 27, 2021

Author: Markus Levy

The last few years have seen an assortment of novel chips and architectures described as neuromorphic or brain-like, some employing a technology called a spiking neural network (SNN). At the recent Linley Spring Processor Conference, Innatera Nanosystems disclosed architectural details of its Spiking Neural Processor, an ultra-low-power pattern recognizer built on a segmented array of analog synapses. Although the startup withheld details, the forthcoming chip will combine its SNN architecture with a set of on-chip peripherals and I/O.

Innatera’s neuromorphic architecture operates at extremely low power, especially compared with deep-learning accelerators (DLAs). To demonstrate the power advantages of its approach, the company used an SNN containing approximately 128 nodes to perform time-series signal classification on 16 temporal patterns; this inference consumed only 100 microwatts (Innatera declined to reveal performance numbers). Its power-efficient architecture can be embedded into edge sensors to support applications such as speech processing in human/machine interfaces, health monitoring in wearable devices, target recognition in radars and lidars, and fault detection in industrial and automotive equipment.

CEO Sumeet Kumar, Chief Scientist Amir Zjajo, Chief Adviser Rene van Leuken, and COO Uma Mahesh founded Innatera in 2018. The Dutch company is a spinoff of Delft University and is part of Delft Enterprises. Its architecture applies knowledge gained over a decade of advanced research in neuromorphic and energy-efficient computing. Innatera has grown to 20 employees and is operating on advance fees from customers as well as a $6 million seed investment from two German venture funds. It expects to receive samples of its first chip in 2H21 and to begin production in 2022.

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