Presentation

Straintronics: Energy Efficient Nanomagnetic Computing

Jayasimha Atulasimha • Supriyo Bandyopadhyay • Md Mamun Al-Rashid

10:00 - 10:45 | Tuesday 25 July 2017 | Grand Ballroom #4

Manuscript

Summary

Many of today’s computing challenges (protein folding, decoding the human genome, weather forecasting, predicting stock market behavior) require massive computational resources and cognitive computing capability. Two roadblocks to such advances are: (1) the excessive energy dissipation that occurs in performing a computation, and (2) the inability of the same device to perform a computation and then store the result in-situ, thereby doubling as both logic and memory. “Straintronics” or strain switched nanomagnetic computing has potential to overcome both road blocks as it is energy efficient and non-volatile. We have recently demonstrated strain clocked nanomagnetic logic in Co nanomagnets [1] patterned on a PMN-PT substrate and surface acoustic wave (SAW) driven manipulation of the magnetic states of single domain nanomagnets [2]. This talk will discuss both the above experimental work as well detailed simulation of strain triggered magnetization dynamics in the presence of thermal noise to implement energy efficient non-volatile computing devices that switch reliably at room temperature. This talk will also explore the use of strain to swith the soft layer of magnetic tunnel junctions[a] (MTJs) and various non-Boolean computing devices and architectures[b] that can be implemnted from such straintronic MTJs (s-MTJs). We will also discuss the key challanges that need to be overcome to make these extremely low energy and non-volatile nanomagnetic switching paradigms viable for practical computing devices. References: [1] Nano Letters, 16, 1069, 2016. [2] Nano Letters, 16, 5681, 2016. Acknowledgement: This work is support by NSF under the NEB2020 grant ECCS-1124714, CAREER grant CCF-1253370 and SHF Grant CCF-1216614 as well as the Semiconductor Research Corporation under NRI task 2203.001. [a,b] Some of the work presented is in collaboration with (a) Prof. Jianping Wang, Univ. of Minnesota; (b)Prof. Csaba Andras Moritz, Univ. of Massachusetts at Amherst and Prof. Amit Ranjan Trivedi, Univ. of Illinois.