Technology Mapping for Circuit Optimization Using Content-Addressable Memory

The growing complexity of Field Programmable Gate Arrays (FPGA's) is leading to architectures with high input cardinality look-up tables (LUT's). This thesis describes a methodology for area-minimizing technology mapping for combinational logic, specifically designed for such FPGA architectures. This methodology, called LURU, leverages the parallel search capabilities of Content-Addressable Memories (CAM's) to outperform traditional mapping algorithms in both execution time and quality of results. The LURU algorithm is fundamentally different from other techniques for technology mapping in that LURU uses textual string representations of circuit topology in order to efficiently store and search for circuit patterns in a CAM. A circuit is mapped to the target LUT technology using both exact and inexact string matching techniques. Common subcircuit expressions (CSE's) are also identified and used for architectural optimization---a small set of CSE's is shown to effectively cover an average of 96% of the test circuits. LURU was tested with the ISCAS'85 suite of combinational benchmark circuits and compared with the mapping algorithms FlowMap and CutMap. The area reduction shown by LURU is, on average, 20% better compared to FlowMap and CutMap. The asymptotic runtime complexity of LURU is shown to be better than that of both FlowMap and CutMap

Hierarchical probabilistic macromodeling for QCA circuits

With the goal of building an hierarchical design methodology for quantum-dot cellular automata (QCA) circuits, we put forward a novel, theoretically sound, method for abstracting the behavior of circuit components in QCA circuit, such as majority logic, lines, wire-taps, cross-overs, inverters, and corners, using macromodels. Recognizing that the basic operation of QCA is probabilistic in nature, we propose probabilistic macromodels for standard QCA circuit elements based on conditional probability characterization, defined over the output states given the input states. Any circuit model is constructed by chaining together the individual logic element macromodels, forming a Bayesian network, defining a joint probability distribution over the whole circuit. We demonstrate three uses for these macromodel-based circuits. First, the probabilistic macromodels allow us to model the logical function of QCA circuits at an abstract level - the "circuit" level - above the current practice of layout level in a time and space efficient manner. We show that the circuit level model is orders of magnitude faster and requires less space than layout level models, making the design and testing of large QCA circuits efficient and relegating the costly full quantum-mechanical simulation of the temporal dynamics to a later stage in the design process. Second, the probabilistic macromodels abstract crucial device level characteristics such as polarization and low-energy error state configurations at the circuit level. We demonstrate how this macromodel-based circuit level representation can be used to infer the ground state probabilities, i.e., cell polarizations, a crucial QCA parameter. This allows us to study the thermal behavior of QCA circuits at a higher level of abstraction. Third, we demonstrate the use of these macromodels for error analysis. We show that low-energy state configurations of the macromodel circuit match those of the layout level, thus allowing us to isolate weak p- oints in circuits design at the circuit level itsel

Design Automation and Design Space Exploration for Quantum Computers

A major hurdle to the deployment of quantum linear systems algorithms and recent quantum simulation algorithms lies in the difficulty to find inexpensive reversible circuits for arithmetic using existing hand coded methods. Motivated by recent advances in reversible logic synthesis, we synthesize arithmetic circuits using classical design automation flows and tools. The combination of classical and reversible logic synthesis enables the automatic design of large components in reversible logic starting from well-known hardware description languages such as Verilog. As a prototype example for our approach we automatically generate high quality networks for the reciprocal $1/x$, which is necessary for quantum linear systems algorithms.Comment: 6 pages, 1 figure, in 2017 Design, Automation & Test in Europe Conference & Exhibition, DATE 2017, Lausanne, Switzerland, March 27-31, 201

Logic Synthesis as an Efficient Means of Minimal Model Discovery from Multivariable Medical Datasets

In this paper we review the application of logic synthesis methods for uncovering minimal structures in observational/medical datasets. Traditionally used in digital circuit design, logic synthesis has taken major strides in the past few decades and forms the foundation of some of the most powerful concepts in computer science and data mining. Here we provide a review of current state of research in application of logic synthesis methods for data analysis and provide a demonstrative example for systematic application and reasoning based on these methods

Verilog-to-PyG -- A Framework for Graph Learning and Augmentation on RTL Designs

The complexity of modern hardware designs necessitates advanced methodologies for optimizing and analyzing modern digital systems. In recent times, machine learning (ML) methodologies have emerged as potent instruments for assessing design quality-of-results at the Register-Transfer Level (RTL) or Boolean level, aiming to expedite design exploration of advanced RTL configurations. In this presentation, we introduce an innovative open-source framework that translates RTL designs into graph representation foundations, which can be seamlessly integrated with the PyTorch Geometric graph learning platform. Furthermore, the Verilog-to-PyG (V2PYG) framework is compatible with the open-source Electronic Design Automation (EDA) toolchain OpenROAD, facilitating the collection of labeled datasets in an utterly open-source manner. Additionally, we will present novel RTL data augmentation methods (incorporated in our framework) that enable functional equivalent design augmentation for the construction of an extensive graph-based RTL design database. Lastly, we will showcase several using cases of V2PYG with detailed scripting examples. V2PYG can be found at \url{https://yu-maryland.github.io/Verilog-to-PyG/}.Comment: 8 pages, International Conference on Computer-Aided Design (ICCAD'23

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

Bayesian macromodeling for circuit level QCA design

We present a probabilistic methodology to model and abstract the behavior of quantum-dot cellular automata circuit(QCA) at “ circuit level” above the current practice of layout level. These macromodels provide input-output relationship of components (a set of QCA cells emulating a logical function) that are faithful to the underlying quantum effects. We show the macromodeling of a few key circuit components in QCA circuit, such as majority logic, lines, wire-taps, cross-overs, inverters, and corners. In this work, we demostrate how we can make use of these macromodels to abstract the logical function of QCA circuits and to extract crucial device level characteristics such as polarization and low-energy error state configurations by circuit level Bayesian model, accurately accounting for temperature and other device level parameters. We also demonstrate how this macromodel based design can be used effectively in analysing and isolating the weak spots in the design at circuit level itself