Researchers have made significant advances in memristor technology, enhancing its precision and efficiency. This innovation promises to bridge the gap between analog and digital computing, offering faster, more energy-efficient processing suitable for AI, machine learning, and beyond. Credit: SciTechDaily.com
Design combines the best of digital and analog computing and delivers >10x energy efficiency.
While most of computing in the world is still digital, the data around us is captured in analog via sensors–images through cameras, temperature, and sound, for example and has to be converted in a digital form for precision. But imagine an autonomous vehicle that needs to capture what’s on the road etc. and then make decisions instantaneously, this data needs to be converted—very quickly with low energy and high precision. What if newly designed analog chips could provide the precision of digital computing with the energy-saving and high-speed advantages of analog computing?
Advances in Memristor Technology
If a computer chip is made up of various circuits, a memristor is a relatively small-sized component of a circuit that stores and processes data very efficiently. In a previous paper from the lab of Founded in 1880, the University of Southern California is one of the world's leading private research universities. It is located in the heart of Los Angeles.
” data-gt-translate-attributes='[{“attribute”:”data-cmtooltip”, “format”:”html”}]’ tabindex=”0″ role=”link”>USC Viterbi School of Engineering Electrical and Computer Engineering professor, J. Joshua Yang, researchers were able to tweak a memristor to achieve unprecedented precision.
His lab within USC Viterbi and its School of Advanced Computing is focused on developing devices for computing. The lab has designed a new circuit and architecture to achieve even higher precision with the same memristors, which could greatly extend the applications of such technology beyond the traditional low-precision territory, such as neural networks. Moreover, says Yang, this innovation is applicable to other types of memory technologies as well, including magnetic memories that use the same device as the read-head of the magnetic hard disk drives, and phase change memories that use the same material as the compact discs (CDs).
Enabling Faster, More Efficient Computing
Normally, says Yang, it is very challenging to quickly program an analog device precisely to a target value. Yang’s lab developed circuit architecture and corresponding algorithm to do exactly that. This innovation makes analog computing using analog devices much more attractive for many applications. Yang says it has, ‘higher efficiency and higher speed with SciTechDaily