Eta adds spiking neural network support to MCU: Page 2 of 2

October 16, 2018 // By Peter Clarke
Eta Compute Inc. (Westlake Village, Calif.) a startup that uses self-timed, ultra-low voltage electronics, has reworked its Cortex-M3 based microcontroller to better support neural network implementation and spiking neural networks.

"Our patented hardware architecture is combined with our fully customizable algorithms based on both CNN and SNNs to perform machine learning inferencing in hundreds of microwatts," said Nara Srinivasa CTO of Eta Compute, in a statement. "These are being sampled to customers who are integrating them into products such as smart speakers and object detection platforms to deliver machine intelligence to the network edge."

Eta Compute classifies its Tensai MCU as an "edge device" claiming it can support full applications in a single device and differentiates it from some competition that are designed to be part of multiple compment node solutions.

Classification of "edge" and "node" neural network processors. Source: Eta Compute.

Eta Compute SoC with machine learning is sampling now with mass production expected in 1Q19.

Related links and articles:

www.etacompute.com

News articles:

Eta raises funds for spiking neural networks

BrainChip launches spiking neural network SoC

Neuromorphic computing runs on asynchronous Cortex-M3

Self-timed logic is Eta Compute's low-power secret


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