New Data Structures and Algorithms for Logic Synthesis and Verification

The strong interaction between Electronic Design Automation (EDA) tools and Complementary Metal-Oxide Semiconductor (CMOS) technology contributed substantially to the advancement of modern digital electronics. The continuous downscaling of CMOS Field Effect Transistor (FET) dimensions enabled the semiconductor industry to fabricate digital systems with higher circuit density at reduced costs. To keep pace with technology, EDA tools are challenged to handle both digital designs with growing functionality and device models of increasing complexity. Nevertheless, whereas the downscaling of CMOS technology is requiring more complex physical design models, the logic abstraction of a transistor as a switch has not changed even with the introduction of 3D FinFET technology. As a consequence, modern EDA tools are fine tuned for CMOS technology and the underlying design methodologies are based on CMOS logic primitives, i.e., negative unate logic functions. While it is clear that CMOS logic primitives will be the ultimate building blocks for digital systems in the next ten years, no evidence is provided that CMOS logic primitives are also the optimal basis for EDA software. In EDA, the efficiency of methods and tools is measured by different metrics such as (i) the result quality, for example the performance of a digital circuit, (ii) the runtime and (iii) the memory footprint on the host computer. With the aim to optimize these metrics, the accordance to a specific logic model is no longer important. Indeed, the key to the success of an EDA technique is the expressive power of the logic primitives handling and solving the problem, which determines the capability to reach better metrics. In this thesis, we investigate new logic primitives for electronic design automation tools. We improve the efficiency of logic representation, manipulation and optimization tasks by taking advantage of majority and biconditional logic primitives. We develop synthesis tools exploiting the majority and biconditional expressiveness. Our tools show strong results as compared to state-of-the-art academic and commercial synthesis tools. Indeed, we produce the best results for several public benchmarks. On top of the enhanced synthesis power, our methods are the natural and native logic abstraction for circuit design in emerging nanotechnologies, where majority and biconditional logic are the primitive gates for physical implementation. We accelerate formal methods by (i) studying properties of logic circuits and (ii) developing new frameworks for logic reasoning engines. We prove non-trivial dualities for the property checking problem in logic circuits. Our findings enable sensible speed-ups in solving circuit satisfiability. We develop an alternative Boolean satisfiability framework based on majority functions. We prove that the general problem is still intractable but we show practical restrictions that can be solved efficiently. Finally, we focus on reversible logic where we propose a new equivalence checking approach. We exploit the invertibility of computation and the functionality of reversible gates in the formulation of the problem. This enables one order of magnitude speed up, as compared to the state-of-the-art solution. We argue that new approaches to solve EDA problems are necessary, as we have reached a point of technology where keeping pace with design goals is tougher than ever

Logic Synthesis for Established and Emerging Computing

Logic synthesis is an enabling technology to realize integrated computing systems, and it entails solving computationally intractable problems through a plurality of heuristic techniques. A recent push toward further formalization of synthesis problems has shown to be very useful toward both attempting to solve some logic problems exactly--which is computationally possible for instances of limited size today--as well as creating new and more powerful heuristics based on problem decomposition. Moreover, technological advances including nanodevices, optical computing, and quantum and quantum cellular computing require new and specific synthesis flows to assess feasibility and scalability. This review highlights recent progress in logic synthesis and optimization, describing models, data structures, and algorithms, with specific emphasis on both design quality and emerging technologies. Example applications and results of novel techniques to established and emerging technologies are reported

New Logic Synthesis As Nanotechnology Enabler (invited paper)

Nanoelectronics comprises a variety of devices whose electrical properties are more complex as compared to CMOS, thus enabling new computational paradigms. The potentially large space for innovation has to be explored in the search for technologies that can support large-scale and high- performance circuit design. Within this space, we analyze a set of emerging technologies characterized by a similar computational abstraction at the design level, i.e., a binary comparator or a majority voter. We demonstrate that new logic synthesis techniques, natively supporting this abstraction, are the technology enablers. We describe models and data-structures for logic design using emerging technologies and we show results of applying new synthesis algorithms and tools. We conclude that new logic synthesis methods are required to both evaluate emerging technologies and to achieve the best results in terms of area, power and performance

Approximate In-memory computing on RERAMs

Computing systems have seen tremendous growth over the past few decades in their capabilities, efficiency, and deployment use cases. This growth has been driven by progress in lithography techniques, improvement in synthesis tools, architectures and power management. However, there is a growing disparity between computing power and the demands on modern computing systems. The standard Von-Neuman architecture has separate data storage and data processing locations. Therefore, it suffers from a memory-processor communication bottleneck, which is commonly referred to as the \u27memory wall\u27. The relatively slower progress in memory technology compared with processing units has continued to exacerbate the memory wall problem. As feature sizes in the CMOS logic family reduce further, quantum tunneling effects are becoming more prominent. Simultaneously, chip transistor density is already so high that all transistors cannot be powered up at the same time without violating temperature constraints, a phenomenon characterized as dark-silicon. Coupled with this, there is also an increase in leakage currents with smaller feature sizes, resulting in a breakdown of \u27Dennard\u27s\u27 scaling. All these challenges cannot be met without fundamental changes in current computing paradigms. One viable solution is in-memory computing, where computing and storage are performed alongside each other. A number of emerging memory fabrics such as ReRAMS, STT-RAMs, and PCM RAMs are capable of performing logic in-memory. ReRAMs possess high storage density, have extremely low power consumption and a low cost of fabrication. These advantages are due to the simple nature of its basic constituting elements which allow nano-scale fabrication. We use flow-based computing on ReRAM crossbars for computing that exploits natural sneak paths in those crossbars. Another concurrent development in computing is the maturation of domains that are error resilient while being highly data and power intensive. These include machine learning, pattern recognition, computer vision, image processing, and networking, etc. This shift in the nature of computing workloads has given weight to the idea of approximate computing , in which device efficiency is improved by sacrificing tolerable amounts of accuracy in computation. We present a mathematically rigorous foundation for the synthesis of approximate logic and its mapping to ReRAM crossbars using search based and graphical methods

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

Automated Synthesis of Memristor Crossbar Networks

The advancement of semiconductor device technology over the past decades has enabled the design of increasingly complex electrical and computational machines. Electronic design automation (EDA) has played a significant role in the design and implementation of transistor-based machines. However, as transistors move closer toward their physical limits, the speed-up provided by Moore\u27s law will grind to a halt. Once again, we find ourselves on the verge of a paradigm shift in the computational sciences as newer devices pave the way for novel approaches to computing. One of such devices is the memristor -- a resistor with non-volatile memory. Memristors can be used as junctional switches in crossbar circuits, which comprise of intersecting sets of vertical and horizontal nanowires. The major contribution of this dissertation lies in automating the design of such crossbar circuits -- doing a new kind of EDA for a new kind of computational machinery. In general, this dissertation attempts to answer the following questions: a. How can we synthesize crossbars for computing large Boolean formulas, up to 128-bit? b. How can we synthesize more compact crossbars for small Boolean formulas, up to 8-bit? c. For a given loop-free C program doing integer arithmetic, is it possible to synthesize an equivalent crossbar circuit? We have presented novel solutions to each of the above problems. Our new, proposed solutions resolve a number of significant bottlenecks in existing research, via the usage of innovative logic representation and artificial intelligence techniques. For large Boolean formulas (up to 128-bit), we have utilized Reduced Ordered Binary Decision Diagrams (ROBDDs) to automatically synthesize linearly growing crossbar circuits that compute them. This cutting edge approach towards flow-based computing has yielded state-of-the-art results. It is worth noting that this approach is scalable to n-bit Boolean formulas. We have made significant original contributions by leveraging artificial intelligence for automatic synthesis of compact crossbar circuits. This inventive method has been expanded to encompass crossbar networks with 1D1M (1-diode-1-memristor) switches, as well. The resultant circuits satisfy the tight constraints of the Feynman Grand Prize challenge and are able to perform 8-bit binary addition. A leading edge development for end-to-end computation with flow-based crossbars has been implemented, which involves methodical translation of loop-free C programs into crossbar circuits via automated synthesis. The original contributions described in this dissertation reflect the substantial progress we have made in the area of electronic design automation for synthesis of memristor crossbar networks

Functional Decomposition Using Majority

Typical operators for the decomposition of Boolean functions in state-of-the-art algorithms are AND, exclusive-OR (XOR), and a 2-to-1 multiplexer (MUX). We propose a logic decomposition algorithm that uses the majority-of-three (MAJ) operation. Such decomposition can extend the capabilities of current logic decomposition, but only found limited attention in previous work. Our algorithm makes use of a decomposition rule based on MAJ. Combined with disjoint-support decomposition, the algorithm can factorize XOR-Majority Graphs (XMGs), a recently proposed data structure which has XOR, MAJ, and inverters as only logic primitives. XMGs have been applied in various applications, including (i) exact synthesis aware rewriting, (ii) pre-optimization for 6-LUT mapping, and (iii) synthesis of quantum networks. An experimental evaluation shows that our algorithm leads to better XMGs compared to state-of-the-art algorithms, which positively affect all these three applications. As one example, our experiments show that the proposed method achieves up to 37.1% with an average of 9.6% reduction on the look-up tables (LUT) size/depth product applied to the EPFL arithmetic benchmarks after technology mapping

Design and synthesis of improved reversible circuits using AIG- and MIG-based graph data structures

Reversible logic synthesis is one of the best suited ways which act as the intermediate step for synthesising Boolean functions on quantum technologies. For a given Boolean function, there are multiple possible intermediate representations (IRs), based on functional abstraction, e.g. truth table, decision diagrams or circuit abstraction, e.g. binary decision diagram (BDD), and-inverter graph (AIG) and majority inverter graph (MIG). These IRs play an important role in building circuits as the choice of an IR directly impacts on cost parameters of the design. In the authors' work, they are analysing the effects of different graphbased IRs (BDD, AIG and MIG) and their usability in making efficient circuit realisations. Although applications of BDDs as an IR to represent large functions has already been studied, here they are demonstrating a synthesis scheme by taking AIG and MIG as IRs and making a comprehensive comparative analysis over all these three graph-based IRs. In experimental evaluation, it is being observed that for small functions BDD gives more compact circuits than the other two IRs but when the input size increases, then MIG as IR makes substantial improvements in cost parameters as compared with BDD by reducing quantum cost by 39% on an average. Along with the experimental results, a detailed analysis over the different IRs is also included to find their easiness in designing circuits