New technology could help solve AI’s ‘memory bottleneck’


Electrical engineers have developed a new magnetic memory device that could potentially support the surge of data-centric computing, which requires ever-increasing power, storage and speed.

Electrical engineers at Northwestern University and the University of Messina in Italy have developed a new magnetic memory device that could potentially support the surge of data-centric computing, which requires ever-increasing power, storage and speed.

Based on antiferromagnetic (AFM) materials, the device is the smallest of its kind ever demonstrated and operates with record-low electrical current to write data.

«The rise of big data has enabled the emergence of artificial intelligence (AI) in the cloud and on edge devices and is fundamentally transforming the computing, networking and data storage industries,» said Northwestern’s Pedram Khalili, who led the research. «However, existing hardware cannot sustain the rapid growth of data-centric computing. Our technology potentially could solve this challenge.»

The research will be published on Feb. 10 in the journal Nature Electronics.

Khalili is an associate professor of electrical and computer engineering in Northwestern’s McCormick School of Engineering. He co-led the study with Giovanni Finocchio, an associate professor of electrical engineering at the University of Messina. The team also included Matthew Grayson, a professor of electrical and computer engineering at McCormick. Jiacheng Shi and Victor Lopez-Dominguez, who are both members of Khalili’s laboratory, served as co-first authors of the paper.


Story Source: Materials provided by Northwestern University. Original written by Amanda Morris. Note: Content may be edited for style and length.


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