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Processing-in-memory (PIM) reduces data transfer latency by rolling memory and logic elements into one compute location. As an emergent material candidate for such an architecture, we propose a strained Weyl semimetal based…

Mesoscale and Nanoscale Physics · Physics 2025-11-20 Youjian Chen , Hamed Vakili , Md Golam Morshed , Avik W. Ghosh

In this paper, the intrinsic physical characteristics of spin-orbit torque (SOT) magnetoresistive random-access memory (MRAM) devices are leveraged to realize sigmoidal neurons in neuromorphic architectures. Performance comparisons with the…

Emerging Technologies · Computer Science 2020-06-03 Brendan Reidy , Ramtin Zand

We propose spin transfer torque--magnetoresistive random access memory (STT-MRAM) based on magneto-resistance and spin transfer torque physics of band-pass spin filtering. Utilizing the electronic analogs of optical phenomena such as…

Mesoscale and Nanoscale Physics · Physics 2019-08-20 Abhishek Sharma , Ashwin Tulapurkar , Bhaskaran Muralidharan

Spin-orbit torque (SOT) enables ultra-fast, energy-efficient magnetization switching, making it a promising mechanism for introducing MRAMs for cache memory applications. However, current SOT-MRAM devices face write efficiency limitations,…

Writing magnetic bits by spin-orbit torques (SOTs) arising from spin Hall effect creates new possibilities for ultrafast and low-power magnetoresistive random access memory (MRAM). For perpendicular MRAM, an extra in-plane field is required…

Applied Physics · Physics 2019-11-25 Yang Liu , Bing Zhou , Zhengkun Dai , Enbo Zhang , Jian-Gang Zhu

Magnetoresistive random access memory (MRAM) technologies with thermally unstable nanomagnets are leveraged to develop an intrinsic stochastic neuron as a building block for restricted Boltzmann machines (RBMs) to form deep belief networks…

Emerging Technologies · Computer Science 2019-04-01 Ramtin Zand , Kerem Y. Camsari , Supriyo Datta , Ronald F. DeMara

Since the discovery of the spin orbit torque (SOT) induced by spin Hall effect in heavy metals, much effort has been devoted to understanding the mechanism of the charge-to-spin conversion as well as to developing new schemes for high…

Mesoscale and Nanoscale Physics · Physics 2022-04-15 Shengjie Shi , R. A. Buhrman

Stochastic spiking neural networks based on nanoelectronic spin devices can be a possible pathway to achieving "brainlike" compact and energy-effcient cognitive intelligence. The computational model attempt to exploit the intrinsic device…

Emerging Technologies · Computer Science 2018-01-29 Chamika M. Liyanagedera , Abhronil Sengupta , Akhilesh Jaiswal , Kaushik Roy

Non-volatile Neuromorphic Computing (NC) elements utilizing Spin Orbit Torque (SOT) provide a viable solution to alleviate the memory wall bottleneck in contemporary computing systems. However, the two challenges, low SOT efficiency and the…

Mesoscale and Nanoscale Physics · Physics 2026-01-26 Badsha Sekh , Hasibur Rahaman , Subhakanta Das , Mitali , Ramu Maddu , Kesavan Jawahar , S. N. Piramanayagam

Spin-Orbit Torque (SOT) Magnetic Random-Access Memory (MRAM) devices offer improved power efficiency, nonvolatility, and performance compared to static RAM, making them ideal, for instance, for cache memory applications. Efficient…

The human brain achieves exceptional energy efficiency by co-locating memory and processing, yet reproducing this principle in hardware remains challenging because many neuromorphic devices require standby power, offer limited…

We present the first experimental demonstration of a neuromorphic network with magnetic tunnel junction (MTJ) synapses, which performs image recognition via vector-matrix multiplication. We also simulate a large MTJ network performing MNIST…

Neural and Evolutionary Computing · Computer Science 2021-12-15 Peng Zhou , Alexander J. Edwards , Fred B. Mancoff , Dimitri Houssameddine , Sanjeev Aggarwal , Joseph S. Friedman

Spin-orbit torque (SOT) represents an energy efficient method to control magnetization in magnetic memory devices. However, deterministically switching perpendicular memory bits usually requires the application of an additional bias field…

Applied Physics · Physics 2018-10-03 Qianchang Wang , John Domann , Guoqiang Yu , Anthony Barra , Kang L. Wang , Gregory P. Carman

Many real-world mission-critical applications require continual online learning from noisy data and real-time decision making with a defined confidence level. Probabilistic models and stochastic neural networks can explicitly handle…

Disordered Systems and Neural Networks · Physics 2022-06-01 Sourav Dutta , Georgios Detorakis , Abhishek Khanna , Benjamin Grisafe , Emre Neftci , Suman Datta

Artificial Neural Networks (ANNs) have found widespread applications in tasks such as pattern recognition and image classification. However, hardware implementations of ANNs using conventional binary arithmetic units are computationally…

Neural and Evolutionary Computing · Computer Science 2017-09-14 Ankit Mondal , Ankur Srivastava

Low barrier nanomagnets have attracted a lot of research interest for their use as sources of high quality true random number generation. More recently, low barrier nanomagnets with tunable output have been shown to be a natural hardware…

Applied Physics · Physics 2020-03-09 Punyashloka Debashis , Rafatul Faria , Kerem Y. Camsari , Supriyo Datta , Zhihong Chen

Synaptic memory is considered to be the main element responsible for learning and cognition in humans. Although traditionally non-volatile long-term plasticity changes have been implemented in nanoelectronic synapses for neuromorphic…

Emerging Technologies · Computer Science 2017-12-20 Abhronil Sengupta , Kaushik Roy

Many key electronic technologies (e.g., large-scale computing, machine learning, and superconducting electronics) require new memories that are fast, reliable, energy-efficient, and of low-impedance at the same time, which has remained a…

Applied Physics · Physics 2020-01-15 Lijun Zhu , Lujun Zhu , Shengjie Shi , D. C. Ralph , R. A. Buhrman

As spin-orbit-torque magnetic random-access memory (SOT-MRAM) is gathering great interest as the next-generation low-power and high-speed on-chip cache memory applications, it is critical to analyze the magnetic tunnel junction (MTJ)…

Applied Physics · Physics 2020-05-28 Xiang Li , Shy-Jay Lin , Mahendra DC , Yu-Ching Liao , Chengyang Yao , Azad Naeemi , Wilman Tsai , Shan X. Wang

Emerging non-volatile memories (NVMs) have currently attracted great interest for their potential applications in advanced low-power information storage and processing technologies. Conventional NVMs, such as magnetic random access memory…