Memristors : a journey from material engineering to beyond Von-Neumann computing

Memristors are a promising building block to the next generation of computing systems. Since 2008, when the physical implementation of a memristor was first postulated, the scientific community has shown a growing interest in this emerging technology. Thus, many other memristive devices have been studied, exploring a large variety of materials and properties. Furthermore, in order to support the design of prac-tical applications, models in different abstract levels have been developed. In fact, a substantial effort has been devoted to the development of memristive based applications, which includes high-density nonvolatile memories, digital and analog circuits, as well as bio-inspired computing. In this context, this paper presents a survey, in hopes of summarizing the highlights of the literature in the last decade

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

LOW POWER CIRCUITS DESIGN USING RESISTIVE NON-VOLATILE MEMORIES

Ph.DDOCTOR OF PHILOSOPH

Heterogeneous Reconfigurable Fabrics for In-circuit Training and Evaluation of Neuromorphic Architectures

A heterogeneous device technology reconfigurable logic fabric is proposed which leverages the cooperating advantages of distinct magnetic random access memory (MRAM)-based look-up tables (LUTs) to realize sequential logic circuits, along with conventional SRAM-based LUTs to realize combinational logic paths. The resulting Hybrid Spin/Charge FPGA (HSC-FPGA) using magnetic tunnel junction (MTJ) devices within this topology demonstrates commensurate reductions in area and power consumption over fabrics having LUTs constructed with either individual technology alone. Herein, a hierarchical top-down design approach is used to develop the HSCFPGA starting from the configurable logic block (CLB) and slice structures down to LUT circuits and the corresponding device fabrication paradigms. This facilitates a novel architectural approach to reduce leakage energy, minimize communication occurrence and energy cost by eliminating unnecessary data transfer, and support auto-tuning for resilience. Furthermore, HSC-FPGA enables new advantages of technology co-design which trades off alternative mappings between emerging devices and transistors at runtime by allowing dynamic remapping to adaptively leverage the intrinsic computing features of each device technology. HSC-FPGA offers a platform for fine-grained Logic-In-Memory architectures and runtime adaptive hardware. An orthogonal dimension of fabric heterogeneity is also non-determinism enabled by either low-voltage CMOS or probabilistic emerging devices. It can be realized using probabilistic devices within a reconfigurable network to blend deterministic and probabilistic computational models. Herein, consider the probabilistic spin logic p-bit device as a fabric element comprising a crossbar-structured weighted array. The Programmability of the resistive network interconnecting p-bit devices can be achieved by modifying the resistive states of the array\u27s weighted connections. Thus, the programmable weighted array forms a CLB-scale macro co-processing element with bitstream programmability. This allows field programmability for a wide range of classification problems and recognition tasks to allow fluid mappings of probabilistic and deterministic computing approaches. In particular, a Deep Belief Network (DBN) is implemented in the field using recurrent layers of co-processing elements to form an n x m1 x m2 x ::: x mi weighted array as a configurable hardware circuit with an n-input layer followed by i ≥ 1 hidden layers. As neuromorphic architectures using post-CMOS devices increase in capability and network size, the utility and benefits of reconfigurable fabrics of neuromorphic modules can be anticipated to continue to accelerate

Reliability-aware circuit design to mitigate impact of device defects and variability in emerging memristor-based applications

In the last decades, semiconductor industry has fostered a fast downscale in technology, propelling the large scale integration of CMOS-based systems. The benefits in miniaturization are numerous, highlighting faster switching frequency, lower voltage supply and higher device density. However, this aggressive scaling trend it has not been without challenges, such as leakage currents, yield reduction or the increase in the overall system power dissipation. New materials, changes in the device structures and new architectures are key to keep the miniaturization trend. It is foreseen that 2D integration will eventually come to an insurmountable physical and economic limit, in which new strategic directions are required, such as the development of new device structures, 3D architectures or heterogeneous systems that takes advantage of the best of different technologies, both the ones already consolidated as well as emergent ones that provide performance and efficiency improvements in applications. In this context, memristor arises as one of several candidates in the race to find suitable emergent devices. Memristor, a blend of the words memory and resistor, is a passive device postulated by Leon Chua in 1971. In contrast with the other fundamental passive elements, memristors have the distinctive feature of modifying their resistance according to the charge that passes through these devices, and remaining unaltered when charge no longer flows. Although when it appeared no physical device implementation was acknowledged, HP Labs claimed in 2008 the manufacture of the first real memristor. This milestone triggered an unexpectedly high research activity about memristors, both in searching new materials and structures as well as in potential applications. Nowadays, memristors are not only appreciated in memory systems by their nonvolatile storage properties, but in many other fields, such as digital computing, signal processing circuits, or non-conventional applications like neuromorphic computing or chaotic circuits. In spite of their promising features, memristors show a primarily downside: they show significant device variation and limited lifetime due degradation compared with other alternatives. This Thesis explores the challenges that memristor variation and malfunction imposes in potential applications. The main goal is to propose circuits and strategies that either avoid reliability problems or take advantage of them. Throughout a collection of scenarios in which reliability issues are present, their impact is studied by means of simulations. This thesis is contextualized and their objectives are exposed in Chapter 1. In Chapter 2 the memristor is introduced, at both conceptual and experimental levels, and different compact levels are presented to be later used in simulations. Chapter 3 deepens in the phenomena that causes the lack of reliability in memristors, and models that include these defects in simulations are provided. The rest of the Thesis covers different applications. Therefore, Chapter 4 exhibits nonvolatile memory systems, and specifically an online test method for faulty cells. Digital computing is presented in Chapter 5, where a solution for the yield reduction in logic operations due to memristors variability is proposed. Lastly, Chapter 6 reviews applications in the analog domain, and it focuses in the exploitation of results observed in faulty memristor-based interconnect mediums for chaotic systems synchronization purposes. Finally, the Thesis concludes in Chapter 7 along with perspectives about future work.Este trabajo desarrolla un novedoso dispositivo condensador basado en el uso de la nanotecnología. El dispositivo parte del concepto existente de metal-aislador-metal (MIM), pero en lugar de una capa aislante continua, se utilizan nanopartículas dieléctricas. Las nanopartículas son principalmente de óxido de silicio (sílice) y poliestireno (PS) y los valores de diámetro son 255nm y 295nm respectivamente. Las nanopartículas contribuyen a una alta relación superficie/volumen y están fácilmente disponibles a bajo costo. La tecnología de depósito desarrollada en este trabajo se basa en la técnica de electrospray, que es una tecnología de fabricación ascendente (bottom-up) que permite el procesamiento por lotes y logra un buen compromiso entre una gran superficie y un bajo tiempo de depósito. Con el objetivo de aumentar la superficie de depósito, la configuración de electrospray ha sido ajustada para permitir áreas de depósito de 1cm2 a 25cm2. El dispositivo fabricado, los llamados condensadores de metal aislante de nanopartículas (NP-MIM) ofrecen valores de capacidad más altos que un condensador convencional similar con una capa aislante continua. En el caso de los NP-MIM de sílice, se alcanza un factor de hasta 1000 de mejora de la capacidad, mientras que los NP-MIM de poliestireno exhibe una ganancia de capacidad en el rango de 11. Además, los NP-MIM de sílice muestran comportamientos capacitivos en específicos rangos de frecuencias que depende de la humedad y el grosor de la capa de nanopartículas, mientras que los NP-MIM de poliestireno siempre mantienen su comportamiento capacitivo. Los dispositivos fabricados se han caracterizado mediante medidas de microscopía electrónica de barrido (SEM) complementadas con perforaciones de haz de iones focalizados (FIB) para caracterizar la topografía de los NP-MIMs. Los dispositivos también se han caracterizado por medidas de espectroscopia de impedancia, a diferentes temperaturas y humedades. El origen de la capacitancia aumentada está asociado en parte a la humedad en las interfaces de las nanopartículas. Se ha desarrollado un modelo de un circuito basado en elementos distribuidos para ajustar y predecir el comportamiento eléctrico de los NP-MIMs. En resumen, esta tesis muestra el diseño, fabricación, caracterización y modelización de un nuevo y prometedor condensador nanopartículas metal-aislante-metal que puede abrir el camino al desarrollo de una nueva tecnología de supercondensadores MIM

Reliability-aware circuit design to mitigate impact of device defects and variability in emerging memristor-based applications

In the last decades, semiconductor industry has fostered a fast downscale in technology, propelling the large scale integration of CMOS-based systems. The benefits in miniaturization are numerous, highlighting faster switching frequency, lower voltage supply and higher device density. However, this aggressive scaling trend it has not been without challenges, such as leakage currents, yield reduction or the increase in the overall system power dissipation. New materials, changes in the device structures and new architectures are key to keep the miniaturization trend. It is foreseen that 2D integration will eventually come to an insurmountable physical and economic limit, in which new strategic directions are required, such as the development of new device structures, 3D architectures or heterogeneous systems that takes advantage of the best of different technologies, both the ones already consolidated as well as emergent ones that provide performance and efficiency improvements in applications. In this context, memristor arises as one of several candidates in the race to find suitable emergent devices. Memristor, a blend of the words memory and resistor, is a passive device postulated by Leon Chua in 1971. In contrast with the other fundamental passive elements, memristors have the distinctive feature of modifying their resistance according to the charge that passes through these devices, and remaining unaltered when charge no longer flows. Although when it appeared no physical device implementation was acknowledged, HP Labs claimed in 2008 the manufacture of the first real memristor. This milestone triggered an unexpectedly high research activity about memristors, both in searching new materials and structures as well as in potential applications. Nowadays, memristors are not only appreciated in memory systems by their nonvolatile storage properties, but in many other fields, such as digital computing, signal processing circuits, or non-conventional applications like neuromorphic computing or chaotic circuits. In spite of their promising features, memristors show a primarily downside: they show significant device variation and limited lifetime due degradation compared with other alternatives. This Thesis explores the challenges that memristor variation and malfunction imposes in potential applications. The main goal is to propose circuits and strategies that either avoid reliability problems or take advantage of them. Throughout a collection of scenarios in which reliability issues are present, their impact is studied by means of simulations. This thesis is contextualized and their objectives are exposed in Chapter 1. In Chapter 2 the memristor is introduced, at both conceptual and experimental levels, and different compact levels are presented to be later used in simulations. Chapter 3 deepens in the phenomena that causes the lack of reliability in memristors, and models that include these defects in simulations are provided. The rest of the Thesis covers different applications. Therefore, Chapter 4 exhibits nonvolatile memory systems, and specifically an online test method for faulty cells. Digital computing is presented in Chapter 5, where a solution for the yield reduction in logic operations due to memristors variability is proposed. Lastly, Chapter 6 reviews applications in the analog domain, and it focuses in the exploitation of results observed in faulty memristor-based interconnect mediums for chaotic systems synchronization purposes. Finally, the Thesis concludes in Chapter 7 along with perspectives about future work.Este trabajo desarrolla un novedoso dispositivo condensador basado en el uso de la nanotecnología. El dispositivo parte del concepto existente de metal-aislador-metal (MIM), pero en lugar de una capa aislante continua, se utilizan nanopartículas dieléctricas. Las nanopartículas son principalmente de óxido de silicio (sílice) y poliestireno (PS) y los valores de diámetro son 255nm y 295nm respectivamente. Las nanopartículas contribuyen a una alta relación superficie/volumen y están fácilmente disponibles a bajo costo. La tecnología de depósito desarrollada en este trabajo se basa en la técnica de electrospray, que es una tecnología de fabricación ascendente (bottom-up) que permite el procesamiento por lotes y logra un buen compromiso entre una gran superficie y un bajo tiempo de depósito. Con el objetivo de aumentar la superficie de depósito, la configuración de electrospray ha sido ajustada para permitir áreas de depósito de 1cm2 a 25cm2. El dispositivo fabricado, los llamados condensadores de metal aislante de nanopartículas (NP-MIM) ofrecen valores de capacidad más altos que un condensador convencional similar con una capa aislante continua. En el caso de los NP-MIM de sílice, se alcanza un factor de hasta 1000 de mejora de la capacidad, mientras que los NP-MIM de poliestireno exhibe una ganancia de capacidad en el rango de 11. Además, los NP-MIM de sílice muestran comportamientos capacitivos en específicos rangos de frecuencias que depende de la humedad y el grosor de la capa de nanopartículas, mientras que los NP-MIM de poliestireno siempre mantienen su comportamiento capacitivo. Los dispositivos fabricados se han caracterizado mediante medidas de microscopía electrónica de barrido (SEM) complementadas con perforaciones de haz de iones focalizados (FIB) para caracterizar la topografía de los NP-MIMs. Los dispositivos también se han caracterizado por medidas de espectroscopia de impedancia, a diferentes temperaturas y humedades. El origen de la capacitancia aumentada está asociado en parte a la humedad en las interfaces de las nanopartículas. Se ha desarrollado un modelo de un circuito basado en elementos distribuidos para ajustar y predecir el comportamiento eléctrico de los NP-MIMs. En resumen, esta tesis muestra el diseño, fabricación, caracterización y modelización de un nuevo y prometedor condensador nanopartículas metal-aislante-metal que puede abrir el camino al desarrollo de una nueva tecnología de supercondensadores MIM.Postprint (published version

Reliability-aware circuit design to mitigate impact of device defects and variability in emerging memristor-based applications

In the last decades, semiconductor industry has fostered a fast downscale in technology, propelling the large scale integration of CMOS-based systems. The benefits in miniaturization are numerous, highlighting faster switching frequency, lower voltage supply and higher device density. However, this aggressive scaling trend it has not been without challenges, such as leakage currents, yield reduction or the increase in the overall system power dissipation. New materials, changes in the device structures and new architectures are key to keep the miniaturization trend. It is foreseen that 2D integration will eventually come to an insurmountable physical and economic limit, in which new strategic directions are required, such as the development of new device structures, 3D architectures or heterogeneous systems that takes advantage of the best of different technologies, both the ones already consolidated as well as emergent ones that provide performance and efficiency improvements in applications. In this context, memristor arises as one of several candidates in the race to find suitable emergent devices. Memristor, a blend of the words memory and resistor, is a passive device postulated by Leon Chua in 1971. In contrast with the other fundamental passive elements, memristors have the distinctive feature of modifying their resistance according to the charge that passes through these devices, and remaining unaltered when charge no longer flows. Although when it appeared no physical device implementation was acknowledged, HP Labs claimed in 2008 the manufacture of the first real memristor. This milestone triggered an unexpectedly high research activity about memristors, both in searching new materials and structures as well as in potential applications. Nowadays, memristors are not only appreciated in memory systems by their nonvolatile storage properties, but in many other fields, such as digital computing, signal processing circuits, or non-conventional applications like neuromorphic computing or chaotic circuits. In spite of their promising features, memristors show a primarily downside: they show significant device variation and limited lifetime due degradation compared with other alternatives. This Thesis explores the challenges that memristor variation and malfunction imposes in potential applications. The main goal is to propose circuits and strategies that either avoid reliability problems or take advantage of them. Throughout a collection of scenarios in which reliability issues are present, their impact is studied by means of simulations. This thesis is contextualized and their objectives are exposed in Chapter 1. In Chapter 2 the memristor is introduced, at both conceptual and experimental levels, and different compact levels are presented to be later used in simulations. Chapter 3 deepens in the phenomena that causes the lack of reliability in memristors, and models that include these defects in simulations are provided. The rest of the Thesis covers different applications. Therefore, Chapter 4 exhibits nonvolatile memory systems, and specifically an online test method for faulty cells. Digital computing is presented in Chapter 5, where a solution for the yield reduction in logic operations due to memristors variability is proposed. Lastly, Chapter 6 reviews applications in the analog domain, and it focuses in the exploitation of results observed in faulty memristor-based interconnect mediums for chaotic systems synchronization purposes. Finally, the Thesis concludes in Chapter 7 along with perspectives about future work.Este trabajo desarrolla un novedoso dispositivo condensador basado en el uso de la nanotecnología. El dispositivo parte del concepto existente de metal-aislador-metal (MIM), pero en lugar de una capa aislante continua, se utilizan nanopartículas dieléctricas. Las nanopartículas son principalmente de óxido de silicio (sílice) y poliestireno (PS) y los valores de diámetro son 255nm y 295nm respectivamente. Las nanopartículas contribuyen a una alta relación superficie/volumen y están fácilmente disponibles a bajo costo. La tecnología de depósito desarrollada en este trabajo se basa en la técnica de electrospray, que es una tecnología de fabricación ascendente (bottom-up) que permite el procesamiento por lotes y logra un buen compromiso entre una gran superficie y un bajo tiempo de depósito. Con el objetivo de aumentar la superficie de depósito, la configuración de electrospray ha sido ajustada para permitir áreas de depósito de 1cm2 a 25cm2. El dispositivo fabricado, los llamados condensadores de metal aislante de nanopartículas (NP-MIM) ofrecen valores de capacidad más altos que un condensador convencional similar con una capa aislante continua. En el caso de los NP-MIM de sílice, se alcanza un factor de hasta 1000 de mejora de la capacidad, mientras que los NP-MIM de poliestireno exhibe una ganancia de capacidad en el rango de 11. Además, los NP-MIM de sílice muestran comportamientos capacitivos en específicos rangos de frecuencias que depende de la humedad y el grosor de la capa de nanopartículas, mientras que los NP-MIM de poliestireno siempre mantienen su comportamiento capacitivo. Los dispositivos fabricados se han caracterizado mediante medidas de microscopía electrónica de barrido (SEM) complementadas con perforaciones de haz de iones focalizados (FIB) para caracterizar la topografía de los NP-MIMs. Los dispositivos también se han caracterizado por medidas de espectroscopia de impedancia, a diferentes temperaturas y humedades. El origen de la capacitancia aumentada está asociado en parte a la humedad en las interfaces de las nanopartículas. Se ha desarrollado un modelo de un circuito basado en elementos distribuidos para ajustar y predecir el comportamiento eléctrico de los NP-MIMs. En resumen, esta tesis muestra el diseño, fabricación, caracterización y modelización de un nuevo y prometedor condensador nanopartículas metal-aislante-metal que puede abrir el camino al desarrollo de una nueva tecnología de supercondensadores MIM

Integrated Circuits/Microchips

With the world marching inexorably towards the fourth industrial revolution (IR 4.0), one is now embracing lives with artificial intelligence (AI), the Internet of Things (IoTs), virtual reality (VR) and 5G technology. Wherever we are, whatever we are doing, there are electronic devices that we rely indispensably on. While some of these technologies, such as those fueled with smart, autonomous systems, are seemingly precocious; others have existed for quite a while. These devices range from simple home appliances, entertainment media to complex aeronautical instruments. Clearly, the daily lives of mankind today are interwoven seamlessly with electronics. Surprising as it may seem, the cornerstone that empowers these electronic devices is nothing more than a mere diminutive semiconductor cube block. More colloquially referred to as the Very-Large-Scale-Integration (VLSI) chip or an integrated circuit (IC) chip or simply a microchip, this semiconductor cube block, approximately the size of a grain of rice, is composed of millions to billions of transistors. The transistors are interconnected in such a way that allows electrical circuitries for certain applications to be realized. Some of these chips serve specific permanent applications and are known as Application Specific Integrated Circuits (ASICS); while, others are computing processors which could be programmed for diverse applications. The computer processor, together with its supporting hardware and user interfaces, is known as an embedded system.In this book, a variety of topics related to microchips are extensively illustrated. The topics encompass the physics of the microchip device, as well as its design methods and applications

DESIGN AND TEST OF DIGITAL CIRCUITS AND SYSTEMS USING CMOS AND EMERGING RESISTIVE DEVICES

The memristor is an emerging nano-device. Low power operation, high density, scalability, non-volatility, and compatibility with CMOS Technology have made it a promising technology for memory, Boolean implementation, computing, and logic systems. This dissertation focuses on testing and design of such applications. In particular, we investigate on testing of memristor-based memories, design of memristive implementation of Boolean functions, and reliability and design of neuromorphic computing such as neural network. In addition, we show how to modify threshold logic gates to implement more functions. Although memristor is a promising emerging technology but is prone to defects due to uncertainties in nanoscale fabrication. Fast March tests are proposed in Chapter 2 that benefit from fast write operations. The test application time is reduced significantly while simultaneously reducing the average test energy per cell. Experimental evaluation in 45 nm technology show a speed-up of approximately 70% with a decrease in energy by approximately 40%. DfT schemes are proposed to implement the new test methods. In Chapter 3, an Integer Linear Programming based framework to identify current-mode threshold logic functions is presented. It is shown that threshold logic functions can be implemented in CMOS-based current mode logic with reduced transistor count when the input weights are not restricted to be integers. Experimental results show that many more functions can be implemented with predetermined hardware overhead, and the hardware requirement of a large percentage of existing threshold functions is reduced when comparing to the traditional CMOS-based threshold logic implementation. In Chapter 4, a new method to implement threshold logic functions using memristors is presented. This method benefits from the high range of memristor’s resistivity which is used to define different weight values, and reduces significantly the transistor count. The proposed approach implements many more functions as threshold logic gates when comparing to existing implementations. Experimental results in 45 nm technology show that the proposed memristive approach implements threshold logic gates with less area and power consumption. Finally, Chapter 5 focuses on current-based designs for neural networks. CMOS aging impacts the total synaptic current and this impacts the accuracy. Chapter 5 introduces an enhanced memristive crossbar array (MCA) based analog neural network architecture to improve reliability due to the aging effect. A built-in current-based calibration circuit is introduced to restore the total synaptic current. The calibration circuit is a current sensor that receives the ideal reference current for non-aged column and restores the reduced sensed current at each column to the ideal value. Experimental results show that the proposed approach restores the currents with less than 1% precision, and the area overhead is negligible