Samsung Electronics has showcased world’s first in-memory computing based on MRAM (Magnetoresistive Random Access Memory).
The paper on this innovation was published online by Nature on January 12 (GMT) and is set to be published in the upcoming print edition of Nature.
“In-memory computing draws similarity to the brain in the sense that in the brain, computing also occurs within the network of biological memories, or synapses, the points where neurons touch one another,” said Seungchul Jung, the first author of the paper. “While the computing performed by our MRAM network, for now, has a different purpose from the computing performed by the brain, such solid-state memory network may in the future be used as a platform to mimic the brain by modeling the brain’s synapse connectivity.”
Titled ‘A crossbar array of magnetoresistive memory devices for in-memory computing’, this paper showcases Samsung’s leadership in-memory technology and its effort to merge memory and system semiconductors for next-generation artificial intelligence (AI) chips.
The research was led by Samsung Advanced Institute of Technology (SAIT) in close collaboration with Samsung Electronics Foundry Business and Semiconductor R&D Center.
The first author of the paper, Seungchul Jung, Staff Researcher at SAIT, and the co-corresponding authors Donhee Ham, Fellow of SAIT and Professor of Harvard University and Sang Joon Kim, Vice President of Technology at SAIT, spearheaded the research.
The Samsung Electronics researchers have provided a solution to this issue by an architectural innovation. Concretely, they succeeded in developing an MRAM array chip that demonstrates in-memory computing, by replacing the standard, ‘current-sum’ in-memory computing architecture with a new, ‘resistance sum’ in-memory computing architecture, which addresses the problem of small resistances of individual MRAM devices.
Samsung’s research team subsequently tested the performance of this MRAM in-memory computing chip by running it to perform AI computing. The chip achieved an accuracy of 98% in the classification of hand-written digits and a 93% accuracy in detecting faces from scenes.
The researchers have also suggested that not only can this new MRAM chip be used for in-memory computing, but it also can serve as a platform to download biological neuronal networks.
This is along the line of the neuromorphic electronics vision that Samsung’s researchers recently put forward in a perspective paper published in the September 2021 issue of the journal Nature Electronics.