Texas engineers teamed up with the world's largest semiconductor foundry to fabricate and test an emerging memory technology that could help meet the increasing energy demand of artificial intelligence.
Together with Taiwan Semiconductor Manufacturing Company (TSMC), researchers tested SOT-MRAM, a type of memory that can retain information even when power is off. It uses magnetic properties, making it faster while also consuming less energy than other memory technologies.
"The unique combination of speed, energy efficiency and endurance makes SOT-MRAM perfectly suited for AI applications, especially in devices where resources like power and memory are limited," said Sam Liu, the first author of the new paper published in Science Advances and a recent UT Austin Ph.D. graduate. "SOT-MRAM hasn't been considered for AI hardware since it can only hold two states, but we designed it so we can take advantage of the binary state while still being accurate."
The research team tested the chips on various AI tasks, including neural network inference, binary neural network training and probabilistic graph modeling.
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