Area-Efficient Spin-Orbit Torque Magnetic Random-Access Memory

Spin-orbit torque magnetic random-access memory (SOT-MRAM) has shown promising potential to realize reliable, high-speed and energy-efficient on-chip memory. However, conventional SOT-MRAM requires two access transistors per cell. This limits the use of conventional SOT-MRAM in high-density memories. Thus, various architectures in the literature have been proposed to improve the area efficiency of the SOT-MRAM. In this chapter, these proposals are divided into two categories: non-diode-based SOT-MRAM and diode-based SOT-MRAM cells. The non-diode-based proposals may result in a 1-bit effective area saving up to 50% compared to the conventional SOT-MRAM, whereas the diode-based designs may result in 1-bit effective area-saving of up to 75%. However, the area saving may be accompanied by higher energy and reliability issue penalties. Therefore, here, the various proposals in the literature are presented, highlighting the pros and cons of each design. Moreover, the technology requirements to realize these proposals are discussed. Finally, the various designs are evaluated from both cell and system level perspectives

Stochastic Memory Devices for Security and Computing

With the widespread use of mobile computing and internet of things, secured communication and chip authentication have become extremely important. Hardware-based security concepts generally provide the best performance in terms of a good standard of security, low power consumption, and large-area density. In these concepts, the stochastic properties of nanoscale devices, such as the physical and geometrical variations of the process, are harnessed for true random number generators (TRNGs) and physical unclonable functions (PUFs). Emerging memory devices, such as resistive-switching memory (RRAM), phase-change memory (PCM), and spin-transfer torque magnetic memory (STT-MRAM), rely on a unique combination of physical mechanisms for transport and switching, thus appear to be an ideal source of entropy for TRNGs and PUFs. An overview of stochastic phenomena in memory devices and their use for developing security and computing primitives is provided. First, a broad classification of methods to generate true random numbers via the stochastic properties of nanoscale devices is presented. Then, practical implementations of stochastic TRNGs, such as hardware security and stochastic computing, are shown. Finally, future challenges to stochastic memory development are discussed

Normally-Off Computing Design Methodology Using Spintronics: From Devices to Architectures

Energy-harvesting-powered computing offers intriguing and vast opportunities to dramatically transform the landscape of Internet of Things (IoT) devices and wireless sensor networks by utilizing ambient sources of light, thermal, kinetic, and electromagnetic energy to achieve battery-free computing. In order to operate within the restricted energy capacity and intermittency profile of battery-free operation, it is proposed to innovate Elastic Intermittent Computation (EIC) as a new duty-cycle-variable computing approach leveraging the non-volatility inherent in post-CMOS switching devices. The foundations of EIC will be advanced from the ground up by extending Spin Hall Effect Magnetic Tunnel Junction (SHE-MTJ) device models to realize SHE-MTJ-based Majority Gate (MG) and Polymorphic Gate (PG) logic approaches and libraries, that leverage intrinsic-non-volatility to realize middleware-coherent, intermittent computation without checkpointing, micro-tasking, or software bloat and energy overheads vital to IoT. Device-level EIC research concentrates on encapsulating SHE-MTJ behavior with a compact model to leverage the non-volatility of the device for intrinsic provision of intermittent computation and lifetime energy reduction. Based on this model, the circuit-level EIC contributions will entail the design, simulation, and analysis of PG-based spintronic logic which is adaptable at the gate-level to support variable duty cycle execution that is robust to brief and extended supply outages or unscheduled dropouts, and development of spin-based research synthesis and optimization routines compatible with existing commercial toolchains. These tools will be employed to design a hybrid post-CMOS processing unit utilizing pipelining and power-gating through state-holding properties within the datapath itself, thus eliminating checkpointing and data transfer operations

A magneto-mechanical accelerometer based on magnetic tunnel junctions

Accelerometers have widespread applications and are an essential component in many areas such as automotive, consumer electronics and industrial applications. Most commercial accelerometers are based on micro-electromechanical system (MEMS) that are limited in downscaling and power consumption. Spintronics-based accelerometers have been proposed as alternatives, however, current proposals suffer from design limitations that result in reliability issues and high cost. Here we propose spintronic accelerometers with magnetic tunnel junctions (MTJs) as building block, which map accelerations into a measurable voltage across the MTJ terminals. The device exploits elastic and dipolar coupling as a sensing mechanism and the spintronic diode effect for the direct read out of the acceleration. The proposed technology represents a potentially competitive and scalable solution to current capacitive MEMS-based approaches that could lead to a step forward in many of the commercial applications.Comment: main document with 4 figures + supplemental informatio

Energy-Efficient In-Memory Architectures Leveraging Intrinsic Behaviors of Embedded MRAM Devices

For decades, innovations to surmount the processor versus memory gap and move beyond conventional von Neumann architectures continue to be sought and explored. Recent machine learning models still expend orders of magnitude more time and energy to access data in memory in addition to merely performing the computation itself. This phenomenon referred to as a memory-wall bottleneck, is addressed herein via a completely fresh perspective on logic and memory technology design. The specific solutions developed in this dissertation focus on utilizing intrinsic switching behaviors of embedded MRAM devices to design cross-layer and energy-efficient Compute-in-Memory (CiM) architectures, accelerate the computationally-intensive operations in various Artificial Neural Networks (ANNs), achieve higher density and reduce the power consumption as crucial requirements in future Internet of Things (IoT) devices. The first cross-layer platform developed herein is an Approximate Generative Adversarial Network (ApGAN) designed to accelerate the Generative Adversarial Networks from both algorithm and hardware implementation perspectives. In addition to binarizing the weights, further reduction in storage and computation resources is achieved by leveraging an in-memory addition scheme. Moreover, a memristor-based CiM accelerator for ApGAN is developed. The second design is a biologically-inspired memory architecture. The Short-Term Memory and Long-Term Memory features in biology are realized in hardware via a beyond-CMOS-based learning approach derived from the repeated input information and retrieval of the encoded data. The third cross-layer architecture is a programmable energy-efficient hardware implementation for Recurrent Neural Network with ultra-low power, area-efficient spin-based activation functions. A novel CiM architecture is proposed to leverage data-level parallelism during the evaluation phase. Specifically, we employ an MRAM-based Adjustable Probabilistic Activation Function (APAF) via a low-power tunable activation mechanism, providing adjustable accuracy levels to mimic ideal sigmoid and tanh thresholding along with a matching algorithm to regulate neuronal properties. Finally, the APAF design is utilized in the Long Short-Term Memory (LSTM) network to evaluate the network performance using binary and non-binary activation functions. The simulation results indicate up to 74.5 x 215; energy-efficiency, 35-fold speedup and ~11x area reduction compared with the similar baseline designs. These can form basis for future post-CMOS based non-Von Neumann architectures suitable for intermittently powered energy harvesting devices capable of pushing intelligence towards the edge of computing network

高密度・高速動作可能なSTT-MRAMへ向けたp-MTJのスイッチング過渡現象とアレイ設計指針に関する研究

Tohoku University遠藤哲郎課

ENERGY-EFFICIENT AND SECURE HARDWARE FOR INTERNET OF THINGS (IoT) DEVICES

Internet of Things (IoT) is a network of devices that are connected through the Internet to exchange the data for intelligent applications. Though IoT devices provide several advantages to improve the quality of life, they also present challenges related to security. The security issues related to IoT devices include leakage of information through Differential Power Analysis (DPA) based side channel attacks, authentication, piracy, etc. DPA is a type of side-channel attack where the attacker monitors the power consumption of the device to guess the secret key stored in it. There are several countermeasures to overcome DPA attacks. However, most of the existing countermeasures consume high power which makes them not suitable to implement in power constraint devices. IoT devices are battery operated, hence it is important to investigate the methods to design energy-efficient and secure IoT devices not susceptible to DPA attacks. In this research, we have explored the usefulness of a novel computing platform called adiabatic logic, low-leakage FinFET devices and Magnetic Tunnel Junction (MTJ) Logic-in-Memory (LiM) architecture to design energy-efficient and DPA secure hardware. Further, we have also explored the usefulness of adiabatic logic in the design of energy-efficient and reliable Physically Unclonable Function (PUF) circuits to overcome the authentication and piracy issues in IoT devices. Adiabatic logic is a low-power circuit design technique to design energy-efficient hardware. Adiabatic logic has reduced dynamic switching energy loss due to the recycling of charge to the power clock. As the first contribution of this dissertation, we have proposed a novel DPA-resistant adiabatic logic family called Energy-Efficient Secure Positive Feedback Adiabatic Logic (EE-SPFAL). EE-SPFAL based circuits are energy-efficient compared to the conventional CMOS based design because of recycling the charge after every clock cycle. Further, EE-SPFAL based circuits consume uniform power irrespective of input data transition which makes them resilience against DPA attacks. Scaling of CMOS transistors have served the industry for more than 50 years in providing integrated circuits that are denser, and cheaper along with its high performance, and low power. However, scaling of the transistors leads to increase in leakage current. Increase in leakage current reduces the energy-efficiency of the computing circuits,and increases their vulnerability to DPA attack. Hence, it is important to investigate the crypto circuits in low leakage devices such as FinFET to make them energy-efficient and DPA resistant. In this dissertation, we have proposed a novel FinFET based Secure Adiabatic Logic (FinSAL) family. FinSAL based designs utilize the low-leakage FinFET device along with adiabatic logic principles to improve energy-efficiency along with its resistance against DPA attack. Recently, Magnetic Tunnel Junction (MTJ)/CMOS based Logic-in-Memory (LiM) circuits have been explored to design low-power non-volatile hardware. Some of the advantages of MTJ device include non-volatility, near-zero leakage power, high integration density and easy compatibility with CMOS devices. However, the differences in power consumption between the switching of MTJ devices increase the vulnerability of Differential Power Analysis (DPA) based side-channel attack. Further, the MTJ/CMOS hybrid logic circuits which require frequent switching of MTJs are not very energy-efficient due to the significant energy required to switch the MTJ devices. In the third contribution of this dissertation, we have investigated a novel approach of building cryptographic hardware in MTJ/CMOS circuits using Look-Up Table (LUT) based method where the data stored in MTJs are constant during the entire encryption/decryption operation. Currently, high supply voltage is required in both writing and sensing operations of hybrid MTJ/CMOS based LiM circuits which consumes a considerable amount of energy. In order to meet the power budget in low-power devices, it is important to investigate the novel design techniques to design ultra-low-power MTJ/CMOS circuits. In the fourth contribution of this dissertation, we have proposed a novel energy-efficient Secure MTJ/CMOS Logic (SMCL) family. The proposed SMCL logic family consumes uniform power irrespective of data transition in MTJ and more energy-efficient compared to the state-of-art MTJ/ CMOS designs by using charge sharing technique. The other important contribution of this dissertation is the design of reliable Physical Unclonable Function (PUF). Physically Unclonable Function (PUF) are circuits which are used to generate secret keys to avoid the piracy and device authentication problems. However, existing PUFs consume high power and they suffer from the problem of generating unreliable bits. This dissertation have addressed this issue in PUFs by designing a novel adiabatic logic based PUF. The time ramp voltages in adiabatic PUF is utilized to improve the reliability of the PUF along with its energy-efficiency. Reliability of the adiabatic logic based PUF proposed in this dissertation is tested through simulation based temperature variations and supply voltage variations

EE-ACML: Energy-Efficient Adiabatic CMOS/MTJ Logic for CPA-Resistant IoT Devices

Internet of Things (IoT) devices have strict energy constraints as they often operate on a battery supply. The cryptographic operations within IoT devices consume substantial energy and are vulnerable to a class of hardware attacks known as side-channel attacks. To reduce the energy consumption and defend against side-channel attacks, we propose combining adiabatic logic and Magnetic Tunnel Junctions to form our novel Energy Efficient-Adiabatic CMOS/MTJ Logic (EE-ACML). EE-ACML is shown to be both low energy and secure when compared to existing CMOS/MTJ architectures. EE-ACML reduces dynamic energy consumption with adiabatic logic, while MTJs reduce the leakage power of a circuit. To show practical functionality and energy savings, we designed one round of PRESENT-80 with the proposed EE-ACML integrated with an adiabatic clock generator. The proposed EE-ACML-based PRESENT-80 showed energy savings of 67.24% at 25 MHz and 86.5% at 100 MHz when compared with a previously proposed CMOS/MTJ circuit. Furthermore, we performed a CPA attack on our proposed design, and the key was kept secret

COHERENT/INCOHERENT MAGNETIZATION DYNAMICS OF NANOMAGNETIC DEVICES FOR ULTRA-LOW ENERGY COMPUTING

Nanomagnetic computing devices are inherently nonvolatile and show unique transfer characteristics while their switching energy requirements are on par, if not better than state of the art CMOS based devices. These characteristics make them very attractive for both Boolean and non-Boolean computing applications. Among different strategies employed to switch nanomagnetic computing devices e.g. magnetic field, spin transfer torque, spin orbit torque etc., strain induced switching has been shown to be among the most energy efficient. Strain switched nanomagnetic devices are also amenable for non-Boolean computing applications. Such strain mediated magnetization switching, termed here as “Straintronics”, is implemented by switching the magnetization of the magnetic layer of a magnetostrictive-piezoelectric nanoscale heterostructure by applying an electric field in the underlying piezoelectric layer. The modes of “straintronic” switching: coherent vs. incoherent switching of spins can affect device performance such as speed, energy dissipation and switching error in such devices. There was relatively little research performed on understanding the switching mechanism (coherent vs. incoherent) in xiv straintronic devices and their adaptation for non-Boolean computing, both of which have been studied in this thesis. Detailed studies of the effects of nanomagnet geometry and size on the coherence of the switching process and ultimately device performance of such strain switched nanomagnetic devices have been performed. These studies also contributed in optimizing designs for low energy, low dynamic error operation of straintronic logic devices and identified avenues for further research. A Novel non-Boolean “straintronic” computing device (Ternary Content Addressable Memory, abbreviated as TCAM) has been proposed and evaluated through numerical simulations. This device showed significant improvement over existing CMOS device based TCAM implementation in terms of scaling, energy-delay product, operational simplicity etc. The experimental part of this thesis answered a very fundamental question in strain induced magnetization rotation. Specifically, this experiment studied the variation in magnetization orientation for strain induced magnetization rotation along the thickness of a magnetostrictive thin film using polarized neutron reflectometry and demonstrated non-uniform magnetization rotation along the thickness of the sample. Additional experimental work was performed to lay the groundwork for ultra-low voltage straintronic switching demonstration. Preliminary sample fabrication and characterization that can potentially lead to low voltage (~10-100 mV) operation and local clocking of such devices has been performed