MAR 18, 2024 1:25 PM PDT

Breaking Digital Limits: Memristors Revolutionize Scientific Computing

Digital computing has become the norm in our everyday lives, but their limits are being reached in terms of computing power. Can analog computing step in and outperform them? This is what a recent study published in Science hopes to address as a team of researchers from the University of Southern California, TetraMem Inc., and the University of Massachusetts, Amherst (UMass Amherst) have spent the last decade developing memristors, which are capable of overcoming the computing limits of digital computing. This study holds the potential to help researchers develop more efficient methods in storing data without the drawbacks of holding too much of it, thus creating a clog.

“In this work, we propose and demonstrate a new circuit architecture and programming protocol that can efficiently represent high-precision numbers using a weighted sum of multiple, relatively low-precision analog devices, such as memristors, with a greatly reduced overhead in circuitry, energy and latency compared with existing quantization approaches,” said Dr. Qiangfei Xia, who is a professor of Electrical & Computer Engineering at UMass Amherst and a co-author on the study.

Image of computer chips with the memristor crossbar arrays. (Credit: Qiangfei Xia)

For the study, the collaborative research team has spent the last ten years developing a novel electrical module called a memristor to assist in in-memory computing that decreases the amount of data transfers that occur when computers are performing complex tasks and need to store data elsewhere to complete those tasks. While this most recent study builds off the aforementioned ten years of research, this recent study demonstrates the memristor’s ability to increase accuracy and efficiency compared to digital computing.

“Our research in the past decade has made analog memristor a viable technology,” said Dr. Xia. “It is time to move such a great technology into the semiconductor industry to benefit the broad AI hardware community.”

How will memristors help improve computing efficiency in the coming years and decades? Only time will tell, and this is why we science!

As always, keep doing science & keep looking up!

Sources: Science, EurekAlert! 

About the Author
Master's (MA/MS/Other)
Laurence Tognetti is a six-year USAF Veteran who earned both a BSc and MSc from the School of Earth and Space Exploration at Arizona State University. Laurence is extremely passionate about outer space and science communication, and is the author of "Outer Solar System Moons: Your Personal 3D Journey".
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