Enhanced Hardware Security Using Charge-Based Emerging Device Technology

The emergence of hardware Trojans has largely reshaped the traditional view that the hardware layer can be blindly trusted. Hardware Trojans, which are often in the form of maliciously inserted circuitry, may impact the original design by data leakage or circuit malfunction. Hardware counterfeiting and IP piracy are another two serious issues costing the US economy more than $200 billion annually. A large amount of research and experimentation has been carried out on the design of these primitives based on the currently prevailing CMOS technology. However, the security provided by these primitives comes at the cost of large overheads mostly in terms of area and power consumption. The development of emerging technologies provides hardware security researchers with opportunities to utilize some of the otherwise unusable properties of emerging technologies in security applications. In this dissertation, we will include the security consideration in the overall performance measurements to fully compare the emerging devices with CMOS technology. The first approach is to leverage two emerging devices (Silicon NanoWire and Graphene SymFET) for hardware security applications. Experimental results indicate that emerging device based solutions can provide high level circuit protection with relatively lower performance overhead compared to conventional CMOS counterpart. The second topic is to construct an energy-efficient DPA-resilient block cipher with ultra low-power Tunnel FET. Current-mode logic is adopted as a circuit-level solution to countermeasure differential power analysis attack, which is mostly used in the cryptographic system. The third investigation targets on potential security vulnerability of foundry insider\u27s attack. Split manufacturing is adopted for the protection on radio-frequency (RF) circuit design

Emerging Technology Based Design of Primitives for Hardware Security

Hardware security concerns such as IP piracy and hardware Trojans have triggered research into circuit protection and malicious logic detection from various design perspectives. In this paper, emerging technologies are investigated by leveraging their unique properties for applications in the hardware security domain. Five example circuit structures including camouflaging gates, polymorphic gates, current/voltage based circuit protectors and current-based XOR logic are designed to prove the high efficiency of Silicon NanoWire FETs and Graphene SymFET in applications such as circuit protection and IP piracy prevention. Simulation results indicate that highly efficient and secure circuit structures can be achieved via the use of emerging technologies

Resonant tunneling in double bilayer graphene - WSe2 heterostructures

We demonstrate gate-tunable resonant tunneling and negative differential resistance between two rotationally aligned bilayer graphene sheets separated by bilayer WSe2. We observe large interlayer current densities of 2 uA/um2 and 2.5 uA/um2, and peak-to-valley ratios approaching 4 and 6 at room temperature and 1.5 K, respectively, values that are comparable to epitaxially grown resonant tunneling heterostructures. An excellent agreement between theoretical calculations using a Lorentzian spectral function for the two-dimensional (2D) quasiparticle states, and the experimental data indicates that the interlayer current stems primarily from energy and in-plane momentum conserving 2D-2D tunneling, with minimal contributions from inelastic or non-momentum conserving tunneling. We demonstrate narrow tunneling resonances with intrinsic half-widths of 4 and 6 meV at 1.5 K and 300 K, respectively.Electrical and Computer Engineerin

Design Automation and Application for Emerging Reconfigurable Nanotechnologies

In the last few decades, two major phenomena have revolutionized the electronic industry – the ever-increasing dependence on electronic circuits and the Complementary Metal Oxide Semiconductor (CMOS) downscaling. These two phenomena have been complementing each other in a way that while electronics, in general, have demanded more computations per functional unit, CMOS downscaling has aptly supported such needs. However, while the computational demand is still rising exponentially, CMOS downscaling is reaching its physical limits. Hence, the need to explore viable emerging nanotechnologies is more imperative than ever. This thesis focuses on streamlining the existing design automation techniques for a class of emerging reconfigurable nanotechnologies. Transistors based on this technology exhibit duality in conduction, i.e. they can be configured dynamically either as a p-type or an n-type device on the application of an external bias. Owing to this dynamic reconfiguration, these transistors are also referred to as Reconfigurable Field-Effect Transistors (RFETs). Exploring and developing new technologies just like CMOS, require tackling two main challenges – first, design automation flow has to be modified to enable tailor- made circuit designs. Second, possible application opportunities should be explored where such technologies can outsmart the existing CMOS technologies. This thesis targets the above two objectives for emerging reconfigurable nanotechnologies by proposing approaches for enabling an Electronic Design Automation (EDA) flow for circuits based on RFETs and exploring hardware security as an application that exploits the transistor-level dynamic reconfiguration offered by this technology. This thesis explains the bottom-up approach adopted to propose a logic synthesis flow by identifying new logic gates and circuit design paradigms that can particularly exploit the dynamic reconfiguration offered by these novel nanotechnologies. This led to the subsequent need of finding natural Boolean logic abstraction for emerging reconfigurable nanotechnologies as it is shown that the existing abstraction of negative unate logic for CMOS technologies is sub-optimal for RFETs-based circuits. In this direction, it has been shown that duality in Boolean logic is a natural abstraction for this technology and can truly represent the duality in conduction offered by individual transistors. Finding this abstraction paved the way for defining suitable primitives and proposing various algorithms for logic synthesis and technology mapping. The following step is to explore compatible physical synthesis flow for emerging reconfigurable nanotechnologies. Using silicon nanowire-based RFETs, .lef and .lib files have been provided which can provide an end-to-end flow to generate .GDSII file for circuits exclusively based on RFETs. Additionally, new approaches have been explored to improve placement and routing for circuits based on reconfigurable nanotechnologies. It has been demonstrated how these approaches led to superior results as compared to the native flow meant for CMOS. Lastly, the unique property of transistor-level reconfiguration offered by RFETs is utilized to implement efficient Intellectual Property (IP) protection schemes against adversarial attacks. The ability to control the conduction of individual transistors can be argued as one of the impactful features of this technology and suitably fits into the paradigm of security measures. Prior security schemes based on CMOS technology often come with large overheads in terms of area, power, and delay. In contrast, RFETs-based hardware security measures such as logic locking, split manufacturing, etc. proposed in this thesis, demonstrate affordable security solutions with low overheads. Overall, this thesis lays a strong foundation for the two main objectives – design automation, and hardware security as an application, to push emerging reconfigurable nanotechnologies for commercial integration. Additionally, contributions done in this thesis are made available under open-source licenses so as to foster new research directions and collaborations.:Abstract List of Figures List of Tables 1 Introduction 1.1 What are emerging reconfigurable nanotechnologies? 1.2 Why does this technology look so promising? 1.3 Electronics Design Automation 1.4 The game of see-saw: key challenges vs benefits for emerging reconfigurable nanotechnologies 1.4.1 Abstracting ambipolarity in logic gate designs 1.4.2 Enabling electronic design automation for RFETs 1.4.3 Enhanced functionality: a suitable fit for hardware security applications 1.5 Research questions 1.6 Entire RFET-centric EDA Flow 1.7 Key Contributions and Thesis Organization 2 Preliminaries 2.1 Reconfigurable Nanotechnology 2.1.1 1D devices 2.1.2 2D devices 2.1.3 Factors favoring circuit-flexibility 2.2 Feasibility aspects of RFET technology 2.3 Logic Synthesis Preliminaries 2.3.1 Circuit Model 2.3.2 Boolean Algebra 2.3.3 Monotone Function and the property of Unateness 2.3.4 Logic Representations 3 Exploring Circuit Design Topologies for RFETs 3.1 Contributions 3.2 Organization 3.3 Related Works 3.4 Exploring design topologies for combinational circuits: functionality-enhanced logic gates 3.4.1 List of Combinational Functionality-Enhanced Logic Gates based on RFETs 3.4.2 Estimation of gate delay using the logical effort theory 3.5 Invariable design of Inverters 3.6 Sequential Circuits 3.6.1 Dual edge-triggered TSPC-based D-flip flop 3.6.2 Exploiting RFET’s ambipolarity for metastability 3.7 Evaluations 3.7.1 Evaluation of combinational logic gates 3.7.2 Novel design of 1-bit ALU 3.7.3 Comparison of the sequential circuit with an equivalent CMOS-based design 3.8 Concluding remarks 4 Standard Cells and Technology Mapping 4.1 Contributions 4.2 Organization 4.3 Related Work 4.4 Standard cells based on RFETs 4.4.1 Interchangeable Pull-Up and Pull-Down Networks 4.4.2 Reconfigurable Truth-Table 4.5 Distilling standard cells 4.6 HOF-based Technology Mapping Flow for RFETs-based circuits 4.6.1 Area adjustments through inverter sharings 4.6.2 Technology Mapping Flow 4.6.3 Realizing Parameters For The Generic Library 4.6.4 Defining RFETs-based Genlib for HOF-based mapping 4.7 Experiments 4.7.1 Experiment 1: Distilling standard-cells from a benchmark suite 4.7.2 Experiment 2A: HOF-based mapping . 4.7.3 Experiment 2B: Using the distilled standard-cells during mapping 4.8 Concluding Remarks 5 Logic Synthesis with XOR-Majority Graphs 5.1 Contributions 5.2 Organization 5.3 Motivation 5.4 Background and Preliminaries 5.4.1 Terminologies 5.4.2 Self-duality in NPN classes 5.4.3 Majority logic synthesis 5.4.4 Earlier work on XMG 5.4.5 Classification of Boolean functions 5.5 Preserving Self-Duality 5.5.1 During logic synthesis 5.5.2 During versatile technology mapping 5.6 Advanced Logic synthesis techniques 5.6.1 XMG resubstitution 5.6.2 Exact XMG rewriting 5.7 Logic representation-agnostic Mapping 5.7.1 Versatile Mapper 5.7.2 Support of supergates 5.8 Creating Self-dual Benchmarks 5.9 Experiments 5.9.1 XMG-based Flow 5.9.2 Experimental Setup 5.9.3 Synthetic self-dual benchmarks 5.9.4 Cryptographic benchmark suite 5.10 Concluding remarks and future research directions 6 Physical synthesis flow and liberty generation 6.1 Contributions 6.2 Organization 6.3 Background and Related Work 6.3.1 Related Works 6.3.2 Motivation 6.4 Silicon Nanowire Reconfigurable Transistors 6.5 Layouts for Logic Gates 6.5.1 Layouts for Static Functional Logic Gates 6.5.2 Layout for Reconfigurable Logic Gate 6.6 Table Model for Silicon Nanowire RFETs 6.7 Exploring Approaches for Physical Synthesis 6.7.1 Using the Standard Place & Route Flow 6.7.2 Open-source Flow 6.7.3 Concept of Driver Cells 6.7.4 Native Approach 6.7.5 Island-based Approach 6.7.6 Utilization Factor 6.7.7 Placement of the Island on the Chip 6.8 Experiments 6.8.1 Preliminary comparison with CMOS technology 6.8.2 Evaluating different physical synthesis approaches 6.9 Results and discussions 6.9.1 Parameters Which Affect The Area 6.9.2 Use of Germanium Nanowires Channels 6.10 Concluding Remarks 7 Polymporphic Primitives for Hardware Security 7.1 Contributions 7.2 Organization 7.3 The Shift To Explore Emerging Technologies For Security 7.4 Background 7.4.1 IP protection schemes 7.4.2 Preliminaries 7.5 Security Promises 7.5.1 RFETs for logic locking (transistor-level locking) 7.5.2 RFETs for split manufacturing 7.6 Security Vulnerabilities 7.6.1 Realization of short-circuit and open-circuit scenarios in an RFET-based inverter 7.6.2 Circuit evaluation on sub-circuits 7.6.3 Reliability concerns: A consequence of short-circuit scenario 7.6.4 Implication of the proposed security vulnerability 7.7 Analytical Evaluation 7.7.1 Investigating the security promises 7.7.2 Investigating the security vulnerabilities 7.8 Concluding remarks and future research directions 8 Conclusion 8.1 Concluding Remarks 8.2 Directions for Future Work Appendices A Distilling standard-cells B RFETs-based Genlib C Layout Extraction File (.lef) for Silicon Nanowire-based RFET D Liberty (.lib) file for Silicon Nanowire-based RFET

2022 roadmap on neuromorphic computing and engineering

Modern computation based on von Neumann architecture is now a mature cutting-edge science. In the von Neumann architecture, processing and memory units are implemented as separate blocks interchanging data intensively and continuously. This data transfer is responsible for a large part of the power consumption. The next generation computer technology is expected to solve problems at the exascale with 10$^{18}$ calculations each second. Even though these future computers will be incredibly powerful, if they are based on von Neumann type architectures, they will consume between 20 and 30 megawatts of power and will not have intrinsic physically built-in capabilities to learn or deal with complex data as our brain does. These needs can be addressed by neuromorphic computing systems which are inspired by the biological concepts of the human brain. This new generation of computers has the potential to be used for the storage and processing of large amounts of digital information with much lower power consumption than conventional processors. Among their potential future applications, an important niche is moving the control from data centers to edge devices. The aim of this roadmap is to present a snapshot of the present state of neuromorphic technology and provide an opinion on the challenges and opportunities that the future holds in the major areas of neuromorphic technology, namely materials, devices, neuromorphic circuits, neuromorphic algorithms, applications, and ethics. The roadmap is a collection of perspectives where leading researchers in the neuromorphic community provide their own view about the current state and the future challenges for each research area. We hope that this roadmap will be a useful resource by providing a concise yet comprehensive introduction to readers outside this field, for those who are just entering the field, as well as providing future perspectives for those who are well established in the neuromorphic computing community

Nanoscale electronic devices based on the hybrid stacks of two-dimensional materials and ferroelectric metal oxides

Further scaling of complementary metal-oxide-semiconductor (CMOS) dimensions will soon lead to a tremendous rise in power consumption while limited gain in the performance of integrated circuits. “Beyond-CMOS” devices, based on two-dimensional (2D) materials, can potentially overcome these limitations and further improve the performance, reduce energy consumption, and add novel functionalities to the CMOS platform. In this Ph.D. dissertation, we investigated energy efficient electronic devices based on a new hybrid material platform consisting of two-dimensional materials and ferroelectric metal oxides. The ferroelectric metal oxides provide programmable and non-volatile doping in the 2D materials, while the atomically thin body in 2D materials enables strong electrostatic control over the channel by the polarized ferroelectric metal oxides. We design and demonstrate a new type of classifier using ferroelectric graphene transistors, which can perform the “comparison” function in the analog domain instead of the traditional digital domain. This new type of classifier utilizes the ambipolar transport and zero bandgap of the graphene to perform the absolute difference function, |A-B|, directly. Unlike the image classifier based on silicon CMOS, the classifier based on ferroelectric graphene transistors only needs ONE transistor per pixel, which will significantly reduce chip area and energy consumption. More importantly, the embedded ferroelectric layer in the graphene transistor enables the non-volatile storage of the target image inside the analog device. Therefore, a single graphene transistor can perform both image storage and comparison functions concurrently. This in-memory computing will eliminate the need for frequent image loading/unloading, which will further reduce the power consumption related to the data transfer. We also explored non-volatile reconfigurable devices based on the hybrid stacks of ferroelectric materials and 2D materials. In traditional silicon CMOS, once the device is fabricated, its function is fixed as either an n-type or a p-type transistor. In this work, we show that functionality of this new type of device can be dynamically reconfigured during operation and the reconfiguration is non-volatile and reprogrammable. We have successfully demonstrated the electrostatic controlled reconfigurable devices based on black phosphorus and non-volatile reconfigurable devices based on molybdenum telluride and ferroelectric hafnium zirconium oxides. These reconfigurable devices will enable the logic circuits to evolve their functions on-demand. The 3D monolithic integration of these reconfigurable devices/circuits and memory blocks will enable in-memory computing and reduce the energy consumption and latency related to the transportation of “Big Data”. This work will open a new path toward the design of novel nano-function circuits based on unique material properties that are absent in traditional circuits based on CMOS logic transistors and Von Neumann architectures. These new devices will also enable a new computing paradigm, where the process latency and energy consumption will no longer be limited by the memory bottleneck

Strain-Engineered MOSFETs

This book brings together new developments in the area of strain-engineered MOSFETs using high-mibility substrates such as SIGe, strained-Si, germanium-on-insulator and III-V semiconductors into a single text which will cover the materials aspects, principles, and design of advanced devices, their fabrication and applications. The book presents a full TCAD methodology for strain-engineering in Si CMOS technology involving data flow from process simulation to systematic process variability simulation and generation of SPICE process compact models for manufacturing for yield optimization