Leveraging the Intrinsic Switching Behaviors of Spintronic Devices for Digital and Neuromorphic Circuits

With semiconductor technology scaling approaching atomic limits, novel approaches utilizing new memory and computation elements are sought in order to realize increased density, enhanced functionality, and new computational paradigms. Spintronic devices offer intriguing avenues to improve digital circuits by leveraging non-volatility to reduce static power dissipation and vertical integration for increased density. Novel hybrid spintronic-CMOS digital circuits are developed herein that illustrate enhanced functionality at reduced static power consumption and area cost. The developed spin-CMOS D Flip-Flop offers improved power-gating strategies by achieving instant store/restore capabilities while using 10 fewer transistors than typical CMOS-only implementations. The spin-CMOS Muller C-Element developed herein improves asynchronous pipelines by reducing the area overhead while adding enhanced functionality such as instant data store/restore and delay-element-free bundled data asynchronous pipelines. Spintronic devices also provide improved scaling for neuromorphic circuits by enabling compact and low power neuron and non-volatile synapse implementations while enabling new neuromorphic paradigms leveraging the stochastic behavior of spintronic devices to realize stochastic spiking neurons, which are more akin to biological neurons and commensurate with theories from computational neuroscience and probabilistic learning rules. Spintronic-based Probabilistic Activation Function circuits are utilized herein to provide a compact and low-power neuron for Binarized Neural Networks. Two implementations of stochastic spiking neurons with alternative speed, power, and area benefits are realized. Finally, a comprehensive neuromorphic architecture comprising stochastic spiking neurons, low-precision synapses with Probabilistic Hebbian Plasticity, and a novel non-volatile homeostasis mechanism is realized for subthreshold ultra-low-power unsupervised learning with robustness to process variations. Along with several case studies, implications for future spintronic digital and neuromorphic circuits are presented

Embedding Logic and Non-volatile Devices in CMOS Digital Circuits for Improving Energy Efficiency

abstract: Static CMOS logic has remained the dominant design style of digital systems for more than four decades due to its robustness and near zero standby current. Static CMOS logic circuits consist of a network of combinational logic cells and clocked sequential elements, such as latches and flip-flops that are used for sequencing computations over time. The majority of the digital design techniques to reduce power, area, and leakage over the past four decades have focused almost entirely on optimizing the combinational logic. This work explores alternate architectures for the flip-flops for improving the overall circuit performance, power and area. It consists of three main sections. First, is the design of a multi-input configurable flip-flop structure with embedded logic. A conventional D-type flip-flop may be viewed as realizing an identity function, in which the output is simply the value of the input sampled at the clock edge. In contrast, the proposed multi-input flip-flop, named PNAND, can be configured to realize one of a family of Boolean functions called threshold functions. In essence, the PNAND is a circuit implementation of the well-known binary perceptron. Unlike other reconfigurable circuits, a PNAND can be configured by simply changing the assignment of signals to its inputs. Using a standard cell library of such gates, a technology mapping algorithm can be applied to transform a given netlist into one with an optimal mixture of conventional logic gates and threshold gates. This approach was used to fabricate a 32-bit Wallace Tree multiplier and a 32-bit booth multiplier in 65nm LP technology. Simulation and chip measurements show more than 30% improvement in dynamic power and more than 20% reduction in core area. The functional yield of the PNAND reduces with geometry and voltage scaling. The second part of this research investigates the use of two mechanisms to improve the robustness of the PNAND circuit architecture. One is the use of forward and reverse body biases to change the device threshold and the other is the use of RRAM devices for low voltage operation. The third part of this research focused on the design of flip-flops with non-volatile storage. Spin-transfer torque magnetic tunnel junctions (STT-MTJ) are integrated with both conventional D-flipflop and the PNAND circuits to implement non-volatile logic (NVL). These non-volatile storage enhanced flip-flops are able to save the state of system locally when a power interruption occurs. However, manufacturing variations in the STT-MTJs and in the CMOS transistors significantly reduce the yield, leading to an overly pessimistic design and consequently, higher energy consumption. A detailed analysis of the design trade-offs in the driver circuitry for performing backup and restore, and a novel method to design the energy optimal driver for a given yield is presented. Efficient designs of two nonvolatile flip-flop (NVFF) circuits are presented, in which the backup time is determined on a per-chip basis, resulting in minimizing the energy wastage and satisfying the yield constraint. To achieve a yield of 98%, the conventional approach would have to expend nearly 5X more energy than the minimum required, whereas the proposed tunable approach expends only 26% more energy than the minimum. A non-volatile threshold gate architecture NV-TLFF are designed with the same backup and restore circuitry in 65nm technology. The embedded logic in NV-TLFF compensates performance overhead of NVL. This leads to the possibility of zero-overhead non-volatile datapath circuits. An 8-bit multiply-and- accumulate (MAC) unit is designed to demonstrate the performance benefits of the proposed architecture. Based on the results of HSPICE simulations, the MAC circuit with the proposed NV-TLFF cells is shown to consume at least 20% less power and area as compared to the circuit designed with conventional DFFs, without sacrificing any performance.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

Modélisation compacte et conception de circuit à base de jonction tunnel ferroélectrique et de jonction tunnel magnétique exploitant le transfert de spin assisté par effet Hall de spin

Non-volatile memory (NVM) devices have been attracting intensive research interest since they promise to solve the increasing static power issue caused by CMOS technology scaling. This thesis focuses on two fields related to NVM: the one is the ferroelectric tunnel junction (FTJ), which is a recent emerging NVM device. The other is the spin-Hall-assisted spin-transfer torque (STT), which is a recent proposed write approach for the magnetic tunnel junction (MTJ). Our objective is to develop the compact models for these two technologies and to explore their application in the non-volatile circuits through simulation.First, we investigated physical models describing the electrical behaviors of the FTJ such as tunneling resistance, dynamic ferroelectric switching and memristive response. The accuracy of these physical models is validated by a good agreement with experimental results. In order to develop an electrical model available for the circuit simulation, we programmed the aforementioned physical models with Verilog-A language and integrated them together. The developed electrical model can run on Cadence platform (a standard circuit simulation tool) and faithfully reproduce the behaviors of the FTJ.Then, using the developed FTJ model and STMicroelectronics CMOS design kit, we designed and simulated three types of circuits: i) FTJ-based random access memory (FTRAM), ii) two FTJ-based neuromorphic systems, one of which emulates spike-timing dependent plasticity (STDP) learning rule, the other implements supervised learning of logic functions, iii) FTJ-based Boolean logic block, by which NAND and NOR logic are demonstrated. The influences of the FTJ parameters on the performance of these circuits were analyzed based on simulation results.Finally, we focused on the reversal of the perpendicular magnetization driven by spin-Hall-assisted STT in a three-terminal MTJ. In this scheme, two write currents are applied to generate spin-Hall effect (SHE) and STT. Numerical simulation based on Landau-Lifshitz-Gilbert (LLG) equation demonstrates that the incubation delay of the STT can be eliminated by the strong SHE, resulting in ultrafast magnetization switching without the need to strengthen the STT. We applied this novel write approach to the design of the magnetic flip-flop and full-adder. Performance comparison between the spin-Hall-assisted and the conventional STT magnetic circuits were discussed based on simulation results and theoretical models.Les mémoires non-volatiles (MNV) sont l'objet d'un effort de recherche croissant du fait de leur capacité à limiter la consommation statique, qui obère habituellement la réduction des dimensions dans la technologie CMOS. Dans ce contexte, cette thèse aborde plus spécifiquement deux technologies de mémoires non volatiles : d'une part les jonctions tunnel ferroélectriques (JTF), dispositif non volatil émergent, et d'autre part les dispositifs à transfert de spin (TS) assisté par effet Hall de spin (EHS), approche alternative proposée récemment pour écrire les jonctions tunnel magnétiques (JTM). Mon objectif est de développer des modèles compacts pour ces deux technologies et d'explorer, par simulation, leur intégration dans les circuits non-volatiles.J'ai d'abord étudié les modèles physiques qui décrivent les comportements électriques des JTF : la résistance tunnel, la dynamique de la commutation ferroélectrique et leur comportement memristif. La précision de ces modèles physiques est validée par leur bonne adéquation avec les résultats expérimentaux. Afin de proposer un modèle compatible avec les simulateurs électriques standards, nous j'ai développé les modèles physiques mentionnés ci-dessus en langue Verilog-A, puis je les ai intégrés ensemble. Le modèle électrique que j'ai conçu peut être exploité sur la plate-forme Cadence (un outil standard pour la simulation de circuit). Il reproduit fidèlement les comportements de JTF. Ensuite, en utilisant ce modèle de JTF et le design-kit CMOS de STMicroelectronics, j'ai conçu et simulé trois types de circuits: i) une mémoire vive (RAM) basée sur les JTF, ii) deux systèmes neuromorphiques basés sur les JTF, l'un qui émule la règle d'apprentissage de la plasticité synaptique basée sur le décalage temporel des impulsions neuronale (STDP), l'autre mettant en œuvre l'apprentissage supervisé de fonctions logiques, iii) un bloc logique booléen basé sur les JTF, y compris la démonstration des fonctions logiques NAND et NOR. L'influence des paramètres de la JTF sur les performances de ces circuits a été analysée par simulation. Finalement, nous avons modélisé la dynamique de renversement de l'aimantation dans les dispositifs à anisotropie perpendiculaire à transfert de spin assisté par effet Hall de spin dans un JTM à trois terminaux. Dans ce schéma, deux courants d'écriture sont appliqués pour générer l'EHS et le TS. La simulation numérique basée sur l'équation de Landau-Lifshitz-Gilbert (LLG) démontre que le délai d'incubation de TS peut être éliminé par un fort EHS, conduisant à la commutation ultra-rapide de l'aimantation, sans pour autant requérir une augmentation excessive du TS. Nous avons appliqué cette nouvelle méthode d'écriture à la conception d'une bascule magnétique et d'un additionneur 1 bit magnétique. Les performances des circuits magnétiques assistés par l'EHS ont été comparés à ceux écrits par transfert de spin, par simulation et par une analyse fondée sur le modèle théorique