Nanomagnetic and Spintronic Devices for Energy-Efficient Memory and Computing

Nanomagnetic and Spintronic Devices for Energy-Efficient Memory and Computing PDF

Author: Jayasimha Atulasimha

Publisher: John Wiley & Sons

Published: 2016-02-03

Total Pages: 352

ISBN-13: 1118869249

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Nanomagnetic and spintronic computing devices are strong contenders for future replacements of CMOS. This is an important and rapidly evolving area with the semiconductor industry investing significantly in the study of nanomagnetic phenomena and in developing strategies to pinpoint and regulate nanomagnetic reliably with a high degree of energy efficiency. This timely book explores the recent and on-going research into nanomagnetic-based technology. Key features: Detailed background material and comprehensive descriptions of the current state-of-the-art research on each topic. Focuses on direct applications to devices that have potential to replace CMOS devices for computing applications such as memory, logic and higher order information processing. Discusses spin-based devices where the spin degree of freedom of charge carriers are exploited for device operation and ultimately information processing. Describes magnet switching methodologies to minimize energy dissipation. Comprehensive bibliographies included for each chapter enabling readers to conduct further research in this field. Written by internationally recognized experts, this book provides an overview of a rapidly burgeoning field for electronic device engineers, field-based applied physicists, material scientists and nanotechnologists. Furthermore, its clear and concise form equips readers with the basic understanding required to comprehend the present stage of development and to be able to contribute to future development. Nanomagnetic and Spintronic Devices for Energy-Efficient Memory and Computing is also an indispensable resource for students and researchers interested in computer hardware, device physics and circuits design.

Nanomagnetic and Spintronic Devices for Energy-Efficient Memory and Computing

Nanomagnetic and Spintronic Devices for Energy-Efficient Memory and Computing PDF

Author: Jayasimha Atulasimha

Publisher: John Wiley & Sons

Published: 2016-01-27

Total Pages: 352

ISBN-13: 1118869257

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Nanomagnetic and spintronic computing devices are strong contenders for future replacements of CMOS. This is an important and rapidly evolving area with the semiconductor industry investing significantly in the study of nanomagnetic phenomena and in developing strategies to pinpoint and regulate nanomagnetic reliably with a high degree of energy efficiency. This timely book explores the recent and on-going research into nanomagnetic-based technology. Key features: Detailed background material and comprehensive descriptions of the current state-of-the-art research on each topic. Focuses on direct applications to devices that have potential to replace CMOS devices for computing applications such as memory, logic and higher order information processing. Discusses spin-based devices where the spin degree of freedom of charge carriers are exploited for device operation and ultimately information processing. Describes magnet switching methodologies to minimize energy dissipation. Comprehensive bibliographies included for each chapter enabling readers to conduct further research in this field. Written by internationally recognized experts, this book provides an overview of a rapidly burgeoning field for electronic device engineers, field-based applied physicists, material scientists and nanotechnologists. Furthermore, its clear and concise form equips readers with the basic understanding required to comprehend the present stage of development and to be able to contribute to future development. Nanomagnetic and Spintronic Devices for Energy-Efficient Memory and Computing is also an indispensable resource for students and researchers interested in computer hardware, device physics and circuits design.

Energy Efficient Spintronic Device for Neuromorphic Computation

Energy Efficient Spintronic Device for Neuromorphic Computation PDF

Author: Md Ali Azam

Publisher:

Published: 2019

Total Pages: 65

ISBN-13:

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Future computing will require significant development in new computing device paradigms. This is motivated by CMOS devices reaching their technological limits, the need for non-Von Neumann architectures as well as the energy constraints of wearable technologies and embedded processors. The first device proposal, an energy-efficient voltage-controlled domain wall device for implementing an artificial neuron and synapse is analyzed using micromagnetic modeling. By controlling the domain wall motion utilizing spin transfer or spin orbit torques in association with voltage generated strain control of perpendicular magnetic anisotropy in the presence of Dzyaloshinskii-Moriya interaction (DMI), different positions of the domain wall are realized in the free layer of a magnetic tunnel junction to program different synaptic weights. Additionally, an artificial neuron can be realized by combining this DW device with a CMOS buffer. The second neuromorphic device proposal is inspired by the brain. Membrane potential of many neurons oscillate in a subthreshold damped fashion and fire when excited by an input frequency that nearly equals their Eigen frequency. We investigate theoretical implementation of such "resonate-and-fire" neurons by utilizing the magnetization dynamics of a fixed magnetic skyrmion based free layer of a magnetic tunnel junction (MTJ). Voltage control of magnetic anisotropy or voltage generated strain results in expansion and shrinking of a skyrmion core that mimics the subthreshold oscillation. Finally, we show that such resonate and fire neurons have potential application in coupled nanomagnetic oscillator based associative memory arrays.

Magnetic Domain Wall Devices

Magnetic Domain Wall Devices PDF

Author: Saima Afroz Siddiqui

Publisher:

Published: 2019

Total Pages: 175

ISBN-13:

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Spintronics promises intriguing device paradigms where electron spin is used as the information token instead of its charge counterpart. Spin transfer torque-magnetic random access memory (STT-MRAM) is considered one of the most mature nonvolatile memory technologies for next generation computers. Spin based devices show promises also for beyond-CMOS, in memory computing and neuromorphic accelerators. In the future cognitive era, nonvolatile memories hold the key to solve the bottleneck in the computational performance due to data shuttling between the processing and the memory units. The application of spintronic devices for these purposes requires versatile, scalable device design that is adaptable to emerging material physics. We design, model and experimentally demonstrate spin orbit torque induced magnetic domain wall devices as the building blocks (i.e. linear synaptic weight generator and the nonlinear activation function generator) for in-memory computing, in particular for artificial neural networks. Spin orbit torque driven magnetic tunnel junctions show great promise as energy efficient emerging nonvolatile logic and memory devices. In addition to its energy efficiency, we take advantage of the spin orbit torque induced domain wall motion in magnetic nanowires to demonstrate the linear change in resistances of the synaptic devices. Modifying the spin-orbit torque from a heavy metal or utilizing the size dependent magnetoresistance of tunnel junctions, we also demonstrate a nonlinear activation function for thresholding signals (analog or digitized) between layers for deep learning. The analog modulation of resistances in these devices requires characterizing the resolution of the resistance. Since domain wall in magnetic wires is the nonvolatile data token for these devices, we study the spatial resolution of discrete magnetic domain wall positions in nanowires. The studies on domain wall is further extended to identify energy-efficient and dynamically robust superior magnetic material for ultra-fast and efficient devices for neuromorphic accelerators.

Non-Volatile In-Memory Computing by Spintronics

Non-Volatile In-Memory Computing by Spintronics PDF

Author: Hao Yu

Publisher: Morgan & Claypool Publishers

Published: 2016-12-02

Total Pages: 163

ISBN-13: 1627056440

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Exa-scale computing needs to re-examine the existing hardware platform that can support intensive data-oriented computing. Since the main bottleneck is from memory, we aim to develop an energy-efficient in-memory computing platform in this book. First, the models of spin-transfer torque magnetic tunnel junction and racetrack memory are presented. Next, we show that the spintronics could be a candidate for future data-oriented computing for storage, logic, and interconnect. As a result, by utilizing spintronics, in-memory-based computing has been applied for data encryption and machine learning. The implementations of in-memory AES, Simon cipher, as well as interconnect are explained in details. In addition, in-memory-based machine learning and face recognition are also illustrated in this book.

Energy-efficient and Secure Designs of Spintronic Memory

Energy-efficient and Secure Designs of Spintronic Memory PDF

Author: Anirudh Iyengar

Publisher:

Published: 2018

Total Pages:

ISBN-13:

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With increased integration of technology in our lives, the arms race between chip manufacturers to provide the latest and greatest to entice the consumer, only intensifies. A by-product of this growth is an ever-increasing demand for performance and efficiency. To address this problem CMOS transistors have always been scaled to smaller nodes to fit in more functionality as well as lower the overall energy-footprint of the operation. However, scaling down the size of the transistor is becoming difficult, which in-turn dramatically reduces the profit motive of such an endeavor. Additionally, several new challenges are emerging in integrated circuit (IC) design: mainly leakage power (in caches) and the need for high-bandwidth computing. With this foresight, the industry began investigating alternative memory technologies such as: Resistive RAM (RRAM), Phase Change RAM (PCRAM), Spin Transfer Torque RAM (STTRAM), Domain Wall Memory (DWM), Magnetic RAM (MRAM), Ferroelectric RAM (FeRAM), Memristor etc., that could replace CMOS in cache applications whilst providing non-volatility (to eradicate leakage), high-density (high-bandwidth compute) and high-endurance (long lifetime). A side-effect of incorporating these new memory technologies is the issue of security, privacy and counterfeiting. As the demand for technology increases, the motivation for adversaries to tamper with them for economic, political and social gains will only increase.A major perspective for the beyond CMOS comes from spintronic memory (as per the International Technology Roadmap for Semiconductors) exploiting not only the charge of electrons but more importantly their magnetism, or their spin. STTRAM and DWM offer much potential owing to their high endurance, retention and density while operating at low-voltages. This motivated me to explore various possibilities of spintronic memory (STTRAM and DWM) in the domain of energy-efficiency, security and testing. This thesis addresses: (i) energy-efficient applications and techniques for a system employing spintronic memory; (ii) the security challenges we might face adopting spintronic memory; and (iii) the need for securing traditional CMOS ICs from a counterfeiting as well as a duplication standpoint. In particular, we tackle the problems in energy-efficiency, authentication, privacy and secrecy. The first part of the thesis describes the modeling aspects of spintronic memory i.e. STTRAM and DWM. Then, we present three energy-efficient spintronic memory applications: (i) non-volatile flip-flop (NVFF), (ii) MTJ crossbar using selector diode (SD) and, (iii) pulsed shifting of DWs. Apart from the traditional state retentivity, the proposed NVFF offers protection against unexpected power-cuts allowing for a fluid instant-ON experience. The MTJ crossbar using a MIIM SD allows for a high-density design with the necessary robustness and energy-efficiency demanded by high bandwidth applications. The pulsed shifting technique of DWs reduces the impact of Joule heating in NWs, thus, maintaining energy efficiency without sacrificing performance. In the next part of the thesis we present potential security vulnerabilities side channel analysis and data privacy, of STTRAM and DWM. We present some mitigation techniques to circumvent these issues. Following this, we explore the security aspects of said spintronic memory, by illustrating their potential use as a PUF. Our proposed PUFs exploit the inherently large entropy surrounding the DW NW making them a strong candidate for magnetic memory-based authentication. We then analyze the operation and robustness of the PUFs under varying supply and temperature conditions.Finally, we describe threshold voltage defined CMOS switches for camouflaging logic. By modifying the doping concentration of selective CMOS switches at design-time, we have been able to realize six different logic functionalities. We demonstrate the designs by implementing ring oscillators (RO) in a 65nm node test-chip on which we analyze the impact of supply-voltage, process variation and temperature. Also, we demonstrate how we can reclaim lost performance by tuning the gate voltage under varying temperatures and supply voltages. The difficulty in RE the netlist when a portion of the gates are camouflaged gate is quantified by estimating the time taken for the decamouflaging process. We also describe camouflaged gate selection using controllability and observability conditions. Additionally, an alternative camouflaging technique that operates on charge-trap is described. The advantage of this technique is that the charge trapped in the gate oxide is responsible for gate selection, thus leaving no physical evidence of camouflaging.In summary, this dissertation provides an overview of the design, analysis and applications of STTRAM and DWM for energy-efficiency and enhanced device security.

Spintronics-based Computing

Spintronics-based Computing PDF

Author: Weisheng Zhao

Publisher: Springer

Published: 2015-05-11

Total Pages: 259

ISBN-13: 3319151800

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This book provides a comprehensive introduction to spintronics-based computing for the next generation of ultra-low power/highly reliable logic. It will cover aspects from device to system-level, including magnetic memory cells, device modeling, hybrid circuit structure, design methodology, CAD tools, and technological integration methods. This book is accessible to a variety of readers and little or no background in magnetism and spin electronics are required to understand its content. The multidisciplinary team of expert authors from circuits, devices, computer architecture, CAD and system design reveal to readers the potential of spintronics nanodevices to reduce power consumption, improve reliability and enable new functionality.

Magnetic Memory with Topological Insulators and Ferrimagnetic Insulators

Magnetic Memory with Topological Insulators and Ferrimagnetic Insulators PDF

Author: Qiming Shao

Publisher:

Published: 2019

Total Pages: 251

ISBN-13:

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Ubiquitous smart devices and internet of things create tremendous data every day, shifting computing diagram towards data-driven. Computing and memory units in traditional computers are physically separated, which leads to huge energy cost and time delay. Novel computer architectures bring computing and memory units together for data-intensive applications. These memory units need to be fast, energy efficient, scalable and nonvolatile. This dissertation concerns innovating new types of magnetic memory or spintronic devices to achieve ultrahigh energy efficiency and ultracompact size from a perspective of material and heterostructure design. Especially, we employ quantum materials to enable potentially unprecedented technological advances. The highest energy efficiency of magnetic memory requires the largest charge-to-spin conversion efficiency that allows the minimum power to manipulate the magnetization. We utilize topological surface states of topological insulators (TIs), which have unique spin-momentum locking and thus are highly spin-polarized. We discover giant spin-orbit torques (SOTs) from TIs at room temperature, which are more than one order of magnitude larger than those of traditional heavy metals. We integrate TIs into room temperature magnetic memories, which promises future ultralow power dissipation. SOT characterization methods and related SOT studies on heavy metals, monolayer two-dimensional materials, and magnetic insulators-based heterostructures are discussed in detail. To have the best scaling performance, we investigate emerging topological skyrmions in magnetic thin films, which are arguably the smallest spin texture in nature. While most of the skyrmions are discovered in metallic systems, insulating skyrmions are desired thanks to their lower damping and thus potentially lower power dissipation. We observe high-temperature electronic signatures of skyrmions in magnetic insulators, topological Hall effect, by engineering heterostructures consisting of heavy metals and magnetic insulators. This new platform is essential for exploring fundamental magnon-skyrmion physics and pursuing practical applications based on insulating skyrmions. To have the highest operation speed, we explore compensated ferrimagnetic insulators, which have THz dynamics due to the strong exchange coupling field. We realize energy efficient switching of the ferrimagnetic insulator in both ferrimagnetic and antiferromagnetic states, promising electrical manipulation of ultrafast dynamics.

McGraw-Hill Yearbook of Science and Technology, 2010

McGraw-Hill Yearbook of Science and Technology, 2010 PDF

Author: McGraw-Hill Education

Publisher: McGraw Hill Professional

Published: 2010-01-12

Total Pages: 480

ISBN-13: 0071782982

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Includes coverage of forefront fields such as cell and molecular biology, environmental science, genetics, information technology, nanotechnology, chemistry, and theoretical physics An extensive subject index makes finding information fast and easy Features numerous cross-references to the McGraw-Hill Encyclopedia of Science & Technology and bibliographies of key literature after each article 250+ images, diagrams, and tables enhance the text