|Title||World's First MRAM-Based In-Memory Computing|
|Date||Tuesday January 18, @03:50PM|
|from the have-you-tried-turning-it-off-and-back-on-again...Oh...wait. dept.|
World's first MRAM-based in-memory computing:
Samsung Electronics today announced its demonstration of the world's first in-memory computing based on MRAM (Magnetoresistive Random Access Memory).
[...] In the standard computer architecture, data is stored in memory chips and data computing is executed in separate processor chips.
In contrast, in-memory computing is a new computing paradigm that seeks to perform both data storage and data computing in a memory network. Since this scheme can process a large amount of data stored within the memory network itself without having to move the data, and also because the data processing in the memory network is executed in a highly parallel manner, power consumption is substantially reduced. In-memory computing has thus emerged as one of the promising technologies to realize next-generation low-power AI semiconductor chips.
For this reason, research on in-memory computing has been intensely pursued worldwide. [...] By contrast, it has so far been difficult to use MRAM—another type of non-volatile memory—for in-memory computing despite MRAM's merits such as operation speed, endurance and large-scale production. This difficulty stems from the low resistance of MRAM, due to which MRAM cannot enjoy the power reduction advantage when used in the standard in-memory computing architecture.
The Samsung Electronics researchers have [...] 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 classification of hand-written digits and a 93% accuracy in detecting faces from scenes.
[...] "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 Dr. Seungchul Jung, the first author of the paper. "In fact, 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."
Seungchul Jung, Hyungwoo Lee, Sungmeen Myung, et al. A crossbar array of magnetoresistive memory devices for in-memory computing, Nature (DOI: 10.1038/s41586-021-04196-6)
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