A new optical neuromorphic processor developed by Swinburne University of Technology can operate more than 1000 times faster than any previous processor. The processor for artificial intelligence (AI) functions faster than 10 trillion operations per second (TeraOPs/s).
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The invention could revolutionize neural networks and neuromorphic processing in general. “This breakthrough was achieved with ‘optical micro-combs’, as was our world-record internet data speed reported in May 2020,” said in a statement Swinburne’s Professor David Moss.
Micro-combs are new devices made up of hundreds of infrared lasers all held on a single chip. Compared to other optical sources, they are much smaller, lighter, faster, and cheaper.
The new innovation demonstrated by the Swinburne team uses a single processor while simultaneously interleaving the data in time, wavelength, and spatial dimensions through a single micro-comb chip.
“In the 10 years since I co-invented them, integrated micro-comb chips have become enormously important and it is truly exciting to see them enabling these huge advances in information communication and processing. Micro-combs offer enormous promise for us to meet the world’s insatiable need for information,” added Moss.
Co-lead author of the study Dr. Xingyuan (Mike) Xu explained how this innovative use of micro-combs is giving the researchers a glimpse into the processors of the future.
Cost and energy reductions
Distinguished Professor Arnan Mitchell from RMIT University added that the “technology is applicable to all forms of processing and communications” and will result in significant future cost and energy consumption reductions.
“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 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.”