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Toggle SOT-MRAM Architecture With Self-Terminating Write Operation
Ebenezer C. Usih;Naimul Hassan;Alexander J. Edwards;Felipe Garcia-Sanchez;Pedram Khalili Amiri;Joseph S. Friedman
Toggle spin-orbit torque (SOT)-driven magnetoresistive random access memory (MRAM) with perpendicular anisotropy has a simple material stack and is more robust than directional SOT-MRAM. However, a read-before-write operation is required to use the toggle SOT-MRAM for directional switching, which threatens to increase the write delay. To resolve these issues, we propose a high-speed memory archite...Show More
Physically Secure Logic Locking With Nanomagnet Logic
Alexander J. Edwards;Naimul Hassan;Jared D. Arzate;Alexander N. Chin;Dhritiman Bhattacharya;Mustafa M. Shihab;Peng Zhou;Xuan Hu;Jayasimha Atulasimha;Yiorgos Makris;Joseph S. Friedman
Securing integrated circuits against counterfeiting through logic locking presents the fundamental challenge of protecting a locking key from physical, Boolean satisfiability (SAT)-based, and structural threats. Prior research has mainly focused on enhancing logic locking to thwart SAT-based and structural attacks but overlooked the necessity of robust physical security. Our work introduces a nove...Show More
Purely Spintronic Leaky Integrate-and-Fire Neurons
Wesley H. Brigner;Naimul Hassan;Xuan Hu;Christopher H. Bennett;Felipe Garcia-Sanchez;Matthew J. Marinella;Jean Anne C. Incorvia;Joseph S. Friedman
2022 IEEE International Symposium on Circuits and Systems (ISCAS)
Year: 2022 | Conference Paper |
Cited by: Papers (3)
Neuromorphic computing promises revolutionary improvements over conventional systems for applications that process unstructured information. To fully realize this potential, neuromorphic systems should exploit the biomimetic behavior of emerging nanodevices. In particular, exceptional opportunities are provided by the non-volatility and analog capabilities of spintronic devices. While spintronic d...Show More
Intrinsic Lateral Inhibition Facilitates Winner-Take-All in Domain Wall Racetrack Arrays for Neuromorphic Computing
Can Cui;Otitoaleke G. Akinola;Naimul Hassan;Christopher H. Bennett;Matthew J. Marinella;Joseph S. Friedman;Jean Anne C. Incorvia
2022 IEEE International Symposium on Circuits and Systems (ISCAS)
Year: 2022 | Conference Paper |
Cited by: Papers (2)
Neuromorphic computing is a promising candidate for beyond-von Neumann computer architectures, featuring low power consumption and high parallelism. Lateral inhibition and winner-take-all (WTA) features play a crucial role in neuronal competition of the nervous system as well as neuromorphic hardwares. The domain wall - magnetic tunnel junction (DWMTJ) neuron is an emerging spintronic artificial n...Show More
Physically and Algorithmically Secure Logic Locking with Hybrid CMOS/Nanomagnet Logic Circuits
Alexander J. Edwards;Naimul Hassan;Dhritiman Bhattacharya;Mustafa M. Shihab;Peng Zhou;Xuan Hu;Jayasimha Atulasimha;Yiorgos Makris;Joseph S. Friedman
2022 Design, Automation & Test in Europe Conference & Exhibition (DATE)
Year: 2022 | Conference Paper |
Cited by: Papers (2)
The successful logic locking of integrated circuits requires that the system be secure against both algorithmic and physical attacks. In order to provide resilience against imaging techniques that can detect electrical behavior, we recently proposed an approach for physically and algorithmically secure logic locking with strain-protected nanomagnet logic (NML). While this NML system exhibits physi...Show More
Domain Wall Leaky Integrate-and-Fire Neurons With Shape-Based Configurable Activation Functions
Wesley H. Brigner;Naimul Hassan;Xuan Hu;Christopher H. Bennett;Felipe Garcia-Sanchez;Can Cui;Alvaro Velasquez;Matthew J. Marinella;Jean Anne C. Incorvia;Joseph S. Friedman
CMOS devices display volatile characteristics and are not well suited for analog applications such as neuromorphic computing. Spintronic devices, on the other hand, exhibit both non-volatile and analog features, which are well suited to neuromorphic computing. Consequently, these novel devices are at the forefront of beyond-CMOS artificial intelligence applications. However, a large quantity of th...Show More
Quantized Domain-Wall Magnetic Tunnel Junction (DW-MTJ) Neural Networks Optimized for Rapid, Energy Efficient Edge Inference
Christopher H. Bennett;Samuel Liu;T. Patrick Xiao;Otitoaleke Akinola;Alexander Edwards;Wesley Brigner;Can Cui;Thomas Leonard;Mashid Alamdar;Naimul Hassan;Robin Jacobs-Gedrim;Joseph S Friedman;Jean Anne Incorvia;Matthew J. Marinella
2021 IEEE 16th Nanotechnology Materials and Devices Conference (NMDC)
Year: 2021 | Conference Paper |
Summary form only given, as follows. The complete presentation was not made available for publication as part of the conference proceedings. The increasing complexity of artificial intelligence (AI) models implies a need for new systems that efficiently process deep neural networks (DNNs) [1]. DNNs can efficiently be implemented using crossbars of dense nonvolatile memories (NVMs) [2]. While most ...Show More
Quantized Domain-Wall Magnetic Tunnel Junction (DW-MTJ) Neural Networks Optimized for Rapid, Energy Efficient Edge Inference
Christopher H. Bennett;Samuel Liu;T. Patrick Xiao;Otitoaleke Akinola;Alexander Edwards;Wesley Brigner;Can Cui;Thomas Leonard;Mashid Alamdar;Naimul Hassan;Robin Jacobs-Gedrim;Joseph S Friedman;Jean Anne Incorvia;Matthew J. Marinella
Year: 2021 | Conference Paper |
Secure Logic Locking with Strain-Protected Nanomagnet Logic
Naimul Hassan;Alexander J. Edwards;Dhritiman Bhattacharya;Mustafa M. Shihab;Varun Venkat;Peng Zhou;Xuan Hu;Shamik Kundu;Abraham P. Kuruvila;Kanad Basu;Jayasimha Atulasimha;Yiorgos Makris;Joseph S. Friedman
2021 58th ACM/IEEE Design Automation Conference (DAC)
Year: 2021 | Conference Paper |
Cited by: Papers (4)
Prevention of integrated circuit counterfeiting through logic locking faces the fundamental challenge of securing an obfuscation key against both physical and algorithmic threats. Previous work has focused on strengthening the logic encryption to protect the key against algorithmic attacks, but failed to provide adequate physical security. In this work, we propose a logic locking scheme that lever...Show More
Multilayer Nanomagnet Threshold Logic
Peng Zhou;Luca Gnoli;Mustafa M. Sadriwala;Fabrizio Riente;Giovanna Turvani;Naimul Hassan;Xuan Hu;Marco Vacca;Joseph S. Friedman
Nanomagnet logic (NML) uses dipolar magnetic coupling between nanomagnets to efficiently perform nonvolatile logical operations. As the basis logic element, the three-input minority gate is the simplest threshold logic function. Recent work has explored the potential for increased logical expressivity with a nanomagnet threshold logic family that reduces area, delay, and energy costs. However, as ...Show More
Device Modeling and Circuit Design for Scalable Beyond-CMOS Computing
Xuan Hu;Naimul Hassan;Wesley H. Brigner;Maverick Chauwin;Joseph S. Friedman
2020 IFIP/IEEE 28th International Conference on Very Large Scale Integration (VLSI-SOC)
Year: 2020 | Conference Paper |
Cited by: Papers (3)
Emerging technologies provide potential solutions to overcome the limitations of modern CMOS technologies. Specifically, as power density limitations impede further CMOS scaling, emerging technologies including spintronics, memristors, ambipolar transistors, and other beyond-CMOS devices are promising replacements for conventional CMOS transistors due to features such as non-volatility, low energy...Show More
CMOS-Free Magnetic Domain Wall Leaky Integrate-and-Fire Neurons with Intrinsic Lateral Inhibition
Naimul Hassan;Wesley H. Brigner;Xuan Hu;Otitoaleke G. Akinola;Christopher H. Bennett;Matthew J. Marinella;Felipe Garcia-Sanchez;Jean Anne C. Incorvia;Joseph S. Friedman
2020 IEEE International Symposium on Circuits and Systems (ISCAS)
Year: 2020 | Conference Paper |
Spintronic devices, especially those based on motion of a domain wall (DW) through a ferromagnetic track, have received a significant amount of interest in the field of neuromorphic computing because of their non-volatility and intrinsic current integration capabilities. Many spintronic neurons using this technology have already been proposed, but they also require external circuitry or additional...Show More
Plasticity-Enhanced Domain-Wall MTJ Neural Networks for Energy-Efficient Online Learning
Christopher H. Bennett;T. Patrick Xiao;Can Cui;Naimul Hassan;Otitoaleke G. Akinola;Jean Anne C. Incorvia;Alvaro Velasquez;Joseph S. Friedman;Matthew J. Marinella
2020 IEEE International Symposium on Circuits and Systems (ISCAS)
Year: 2020 | Conference Paper |
Cited by: Papers (2)
Machine learning implements backpropagation via abundant training samples. We demonstrate a multi-stage learning system realized by a promising non-volatile memory device, the domain-wall magnetic tunnel junction (DW-MTJ). The system consists of unsupervised (clustering) as well as supervised sub-systems, and generalizes quickly (with few samples). We demonstrate interactions between physical prop...Show More
Toggle Spin-Orbit Torque MRAM With Perpendicular Magnetic Anisotropy
Naimul Hassan;Susana P. Lainez-Garcia;Felipe Garcia-Sanchez;Joseph S. Friedman
Spin-orbit torque (SOT) is a promising switching mechanism for magnetic random-access memory (MRAM) as a result of the potential for improved switching speed and energy efficiency. It is of particular interest to develop an SOT-MRAM device with perpendicular magnetic anisotropy (PMA) in order to leverage the greater density and thermal stability achievable with PMA as opposed to in-plane magnetic ...Show More
Shape-Based Magnetic Domain Wall Drift for an Artificial Spintronic Leaky Integrate-and-Fire Neuron
Wesley H. Brigner;Naimul Hassan;Lucian Jiang-Wei;Xuan Hu;Diptish Saha;Christopher H. Bennett;Matthew J. Marinella;Jean Anne C. Incorvia;Felipe Garcia-Sanchez;Joseph S. Friedman
Spintronic devices based on domain wall (DW) motion through ferromagnetic nanowire tracks have received great interest as components of neuromorphic information processing systems. Previous proposals for spintronic artificial neurons required external stimuli to perform the leaking functionality, one of the three fundamental functions of a leaky integrate-and-fire (LIF) neuron. The use of this ext...Show More
Graded-Anisotropy-Induced Magnetic Domain Wall Drift for an Artificial Spintronic Leaky Integrate-and-Fire Neuron
Wesley H. Brigner;Xuan Hu;Naimul Hassan;Christopher H. Bennett;Jean Anne C. Incorvia;Felipe Garcia-Sanchez;Joseph S. Friedman
Spintronic three-terminal magnetic-tunnel-junction (3T-MTJ) devices have gained considerable interest in the field of neuromorphic computing. Previously, these devices required external circuitry to implement the leaking functionality that leaky integrate-and-fire (LIF) neurons should display. However, the use of external circuitry results in decreased device efficiency. We previously demonstrated...Show More
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