CAREER: Energy-efficient Magnetic Random Access Memory (MRAM) with All-Superconducting Ope — NSF Award to University of Minnesota-
This project aims to develop a new energy-efficient memory device to address the rapidly growing energy demands of artificial intelligence (AI) and data centers. As AI models become larger and more powerful, the electricity required to train and operate these computational models is growing exponentially and is project
| Award title | CAREER: Energy-efficient Magnetic Random Access Memory (MRAM) with All-Superconducting Ope |
|---|---|
| Award ID | 2540679 |
| Awardee | University of Minnesota-Twin Cities |
| City | MINNEAPOLIS |
| State | MN |
| Amount obligated | $550,000 |
| Principal investigator | Gang Qiu |
| Program | EPMQD: Electronic, Photonic, M |
| Start date | 06/01/2026 |
| Abstract | This project aims to develop a new energy-efficient memory device to address the rapidly growing energy demands of artificial intelligence (AI) and data centers. As AI models become larger and more powerful, the electricity required to train and operate these computational models is growing exponentially and is projected to consume up to 12% of total electricity in the U.S. by 2028. Within this current data-centric computing scheme, non-volatile memory devices that store and retrieve information |
| Source | NSF Awards |
$799/mo
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