The optical neuromorphic processor operates a thousand times faster than previous ones.

A research team led by Swinburne University of Technology Professor David Moss, Swinburne alum Dr. Xingyuan Xu, and Distinguished Professor Arnan Mitchell from RMIT University, has developed what is currently the world’s fastest, most powerful neuromorphic processor for AI. (UNITE.AI)

The new optical neuromorphic processor would be a hugely positive move for AI, particularly neural networks and neuromorphic processing. Operating at speeds of over 10 trillion operations per second (TeraOps/s), it is capable of processing ultra-large-scale images. Conventional processors are unable to process the latter – a limitation in facial recognition.

Microcombs

The researchers used micro-combs in the development of their new processor. A micro-comb is a new optical device that comprises hundreds of high-quality infrared lasers on a single chip.

The team said they achieved a breakthrough using “a new technique of simultaneously interleaving the data in time, wavelength and spatial dimensions through an integrated micro-comb source.”

“We’re currently getting a sneak-peak of how the processors of the future will look,” said co-lead author of the study, Dr. Xu. “It’s really showing us how dramatically we can scale the power of our processors through the innovative use of micro combs.”

Applications

“This processor can serve as a universal ultrahigh bandwidth front end for any neuromorphic hardware — optical or electronic-based — bringing massive-data machine learning for real-time ultra-high bandwidth data within reach,” added Dr. Xu.

“Convolutional neural networks have been central to the artificial intelligence revolution, but existing silicon technology increasingly presents a bottleneck in processing speed and energy efficiency,” said a key supporter of the research team, Professor Damien Hicks, from Swinburne and the Walter and Elizabeth Hall Institute.

“This breakthrough shows how a new optical technology makes such networks faster and more efficient and is a profound demonstration of the benefits of cross-disciplinary thinking, in having the inspiration and courage to take an idea from one field and using it to solve a fundamental problem in another,” he added.

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