AI/ML Algorithms and Applications in VLSI Design and Technology

An evident challenge ahead for the integrated circuit (IC) industry in the nanometer regime is the investigation and development of methods that can reduce the design complexity ensuing from growing process variations and curtail the turnaround time of chip manufacturing. Conventional methodologies employed for such tasks are largely manual; thus, time-consuming and resource-intensive. In contrast, the unique learning strategies of artificial intelligence (AI) provide numerous exciting automated approaches for handling complex and data-intensive tasks in very-large-scale integration (VLSI) design and testing. Employing AI and machine learning (ML) algorithms in VLSI design and manufacturing reduces the time and effort for understanding and processing the data within and across different abstraction levels via automated learning algorithms. It, in turn, improves the IC yield and reduces the manufacturing turnaround time. This paper thoroughly reviews the AI/ML automated approaches introduced in the past towards VLSI design and manufacturing. Moreover, we discuss the scope of AI/ML applications in the future at various abstraction levels to revolutionize the field of VLSI design, aiming for high-speed, highly intelligent, and efficient implementations

The Fifth NASA Symposium on VLSI Design

The fifth annual NASA Symposium on VLSI Design had 13 sessions including Radiation Effects, Architectures, Mixed Signal, Design Techniques, Fault Testing, Synthesis, Signal Processing, and other Featured Presentations. The symposium provides insights into developments in VLSI and digital systems which can be used to increase data systems performance. The presentations share insights into next generation advances that will serve as a basis for future VLSI design

The 1992 4th NASA SERC Symposium on VLSI Design

Papers from the fourth annual NASA Symposium on VLSI Design, co-sponsored by the IEEE, are presented. Each year this symposium is organized by the NASA Space Engineering Research Center (SERC) at the University of Idaho and is held in conjunction with a quarterly meeting of the NASA Data System Technology Working Group (DSTWG). One task of the DSTWG is to develop new electronic technologies that will meet next generation electronic data system needs. The symposium provides insights into developments in VLSI and digital systems which can be used to increase data systems performance. The NASA SERC is proud to offer, at its fourth symposium on VLSI design, presentations by an outstanding set of individuals from national laboratories, the electronics industry, and universities. These speakers share insights into next generation advances that will serve as a basis for future VLSI design

The 1991 3rd NASA Symposium on VLSI Design

Papers from the symposium are presented from the following sessions: (1) featured presentations 1; (2) very large scale integration (VLSI) circuit design; (3) VLSI architecture 1; (4) featured presentations 2; (5) neural networks; (6) VLSI architectures 2; (7) featured presentations 3; (8) verification 1; (9) analog design; (10) verification 2; (11) design innovations 1; (12) asynchronous design; and (13) design innovations 2

Introduction to Logic Circuits & Logic Design with VHDL

The overall goal of this book is to fill a void that has appeared in the instruction of digital circuits over the past decade due to the rapid abstraction of system design. Up until the mid-1980s, digital circuits were designed using classical techniques. Classical techniques relied heavily on manual design practices for the synthesis, minimization, and interfacing of digital systems. Corresponding to this design style, academic textbooks were developed that taught classical digital design techniques. Around 1990, large-scale digital systems began being designed using hardware description languages (HDL) and automated synthesis tools. Broad-scale adoption of this modern design approach spread through the industry during this decade. Around 2000, hardware description languages and the modern digital design approach began to be taught in universities, mainly at the senior and graduate level. There were a variety of reasons that the modern digital design approach did not penetrate the lower levels of academia during this time. First, the design and simulation tools were difficult to use and overwhelmed freshman and sophomore students. Second, the ability to implement the designs in a laboratory setting was infeasible. The modern design tools at the time were targeted at custom integrated circuits, which are cost- and time-prohibitive to implement in a university setting. Between 2000 and 2005, rapid advances in programmable logic and design tools allowed the modern digital design approach to be implemented in a university setting, even in lower-level courses. This allowed students to learn the modern design approach based on HDLs and prototype their designs in real hardware, mainly field programmable gate arrays (FPGAs). This spurred an abundance of textbooks to be authored teaching hardware description languages and higher levels of design abstraction. This trend has continued until today. While abstraction is a critical tool for engineering design, the rapid movement toward teaching only the modern digital design techniques has left a void for freshman- and sophomore-level courses in digital circuitry. Legacy textbooks that teach the classical design approach are outdated and do not contain sufficient coverage of HDLs to prepare the students for follow-on classes. Newer textbooks that teach the modern digital design approach move immediately into high-level behavioral modeling with minimal or no coverage of the underlying hardware used to implement the systems. As a result, students are not being provided the resources to understand the fundamental hardware theory that lies beneath the modern abstraction such as interfacing, gate-level implementation, and technology optimization. Students moving too rapidly into high levels of abstraction have little understanding of what is going on when they click the “compile and synthesize” button of their design tool. This leads to graduates who can model a breadth of different systems in an HDL but have no depth into how the system is implemented in hardware. This becomes problematic when an issue arises in a real design and there is no foundational knowledge for the students to fall back on in order to debug the problem

Introduction to Logic Circuits & Logic Design with Verilog

The overall goal of this book is to fill a void that has appeared in the instruction of digital circuits over the past decade due to the rapid abstraction of system design. Up until the mid-1980s, digital circuits were designed using classical techniques. Classical techniques relied heavily on manual design practices for the synthesis, minimization, and interfacing of digital systems. Corresponding to this design style, academic textbooks were developed that taught classical digital design techniques. Around 1990, large-scale digital systems began being designed using hardware description languages (HDL) and automated synthesis tools. Broad-scale adoption of this modern design approach spread through the industry during this decade. Around 2000, hardware description languages and the modern digital design approach began to be taught in universities, mainly at the senior and graduate level. There were a variety of reasons that the modern digital design approach did not penetrate the lower levels of academia during this time. First, the design and simulation tools were difficult to use and overwhelmed freshman and sophomore students. Second, the ability to implement the designs in a laboratory setting was infeasible. The modern design tools at the time were targeted at custom integrated circuits, which are cost- and time-prohibitive to implement in a university setting. Between 2000 and 2005, rapid advances in programmable logic and design tools allowed the modern digital design approach to be implemented in a university setting, even in lower-level courses. This allowed students to learn the modern design approach based on HDLs and prototype their designs in real hardware, mainly fieldprogrammable gate arrays (FPGAs). This spurred an abundance of textbooks to be authored, teaching hardware description languages and higher levels of design abstraction. This trend has continued until today. While abstraction is a critical tool for engineering design, the rapid movement toward teaching only the modern digital design techniques has left a void for freshman- and sophomore-level courses in digital circuitry. Legacy textbooks that teach the classical design approach are outdated and do not contain sufficient coverage of HDLs to prepare the students for follow-on classes. Newer textbooks that teach the modern digital design approach move immediately into high-level behavioral modeling with minimal or no coverage of the underlying hardware used to implement the systems. As a result, students are not being provided the resources to understand the fundamental hardware theory that lies beneath the modern abstraction such as interfacing, gate-level implementation, and technology optimization. Students moving too rapidly into high levels of abstraction have little understanding of what is going on when they click the “compile and synthesize” button of their design tool. This leads to graduates who can model a breadth of different systems in an HDL but have no depth into how the system is implemented in hardware. This becomes problematic when an issue arises in a real design and there is no foundational knowledge for the students to fall back on in order to debug the problem

Resilience of an embedded architecture using hardware redundancy

In the last decade the dominance of the general computing systems market has being replaced by embedded systems with billions of units manufactured every year. Embedded systems appear in contexts where continuous operation is of utmost importance and failure can be profound. Nowadays, radiation poses a serious threat to the reliable operation of safety-critical systems. Fault avoidance techniques, such as radiation hardening, have been commonly used in space applications. However, these components are expensive, lag behind commercial components with regards to performance and do not provide 100% fault elimination. Without fault tolerant mechanisms, many of these faults can become errors at the application or system level, which in turn, can result in catastrophic failures. In this work we study the concepts of fault tolerance and dependability and extend these concepts providing our own definition of resilience. We analyse the physics of radiation-induced faults, the damage mechanisms of particles and the process that leads to computing failures. We provide extensive taxonomies of 1) existing fault tolerant techniques and of 2) the effects of radiation in state-of-the-art electronics, analysing and comparing their characteristics. We propose a detailed model of faults and provide a classification of the different types of faults at various levels. We introduce an algorithm of fault tolerance and define the system states and actions necessary to implement it. We introduce novel hardware and system software techniques that provide a more efficient combination of reliability, performance and power consumption than existing techniques. We propose a new element of the system called syndrome that is the core of a resilient architecture whose software and hardware can adapt to reliable and unreliable environments. We implement a software simulator and disassembler and introduce a testing framework in combination with ERA’s assembler and commercial hardware simulators

Crosstalk computing: circuit techniques, implementation and potential applications

Title from PDF of title [age viewed January 32, 2022Dissertation advisor: Mostafizur RahmanVitaIncludes bibliographical references (page 117-136)Thesis (Ph.D.)--School of Computing and Engineering. University of Missouri--Kansas City, 2020This work presents a radically new computing concept for digital Integrated Circuits (ICs), called Crosstalk Computing. The conventional CMOS scaling trend is facing device scaling limitations and interconnect bottleneck. The other primary concern of miniaturization of ICs is the signal-integrity issue due to Crosstalk, which is the unwanted interference of signals between neighboring metal lines. The Crosstalk is becoming inexorable with advancing technology nodes. Traditional computing circuits always tries to reduce this Crosstalk by applying various circuit and layout techniques. In contrast, this research develops novel circuit techniques that can leverage this detrimental effect and convert it astutely to a useful feature. The Crosstalk is engineered into a logic computation principle by leveraging deterministic signal interference for innovative circuit implementation. This research work presents a comprehensive circuit framework for Crosstalk Computing and derives all the key circuit elements that can enable this computing model. Along with regular digital logic circuits, it also presents a novel Polymorphic circuit approach unique to Crosstalk Computing. In Polymorphic circuits, the functionality of a circuit can be altered using a control variable. Owing to the multi-functional embodiment in polymorphic-circuits, they find many useful applications such as reconfigurable system design, resource sharing, hardware security, and fault-tolerant circuit design, etc. This dissertation shows a comprehensive list of polymorphic logic gate implementations, which were not reported previously in any other work. It also performs a comparison study between Crosstalk polymorphic circuits and existing polymorphic approaches, which are either inefficient due to custom non-linear circuit styles or propose exotic devices. The ability to design a wide range of polymorphic logic circuits (basic and complex logics) compact in design and minimal in transistor count is unique to Crosstalk Computing, which leads to benefits in the circuit density, power, and performance. The circuit simulation and characterization results show a 6x improvement in transistor count, 2x improvement in switching energy, and 1.5x improvement in performance compared to counterpart implementation in CMOS circuit style. Nevertheless, the Crosstalk circuits also face issues while cascading the circuits; this research analyzes all the problems and develops auxiliary circuit techniques to fix the problems. Moreover, it shows a module-level cascaded polymorphic circuit example, which also employs the auxiliary circuit techniques developed. For the very first time, it implements a proof-of-concept prototype Chip for Crosstalk Computing at TSMC 65nm technology and demonstrates experimental evidence for runtime reconfiguration of the polymorphic circuit. The dissertation also explores the application potentials for Crosstalk Computing circuits. Finally, the future work section discusses the Electronic Design Automation (EDA) challenges and proposes an appropriate design flow; besides, it also discusses ideas for the efficient implementation of Crosstalk Computing structures. Thus, further research and development to realize efficient Crosstalk Computing structures can leverage the comprehensive circuit framework developed in this research and offer transformative benefits for the semiconductor industry.Introduction and Motivation -- More Moore and Relevant Beyond CMOS Research Directions -- Crosstalk Computing -- Crosstalk Circuits Based on Perception Model -- Crosstalk Circuit Types -- Cascading Circuit Issues and Sollutions -- Existing Polymorphic Circuit Approaches -- Crosstalk Polymorphic Circuits -- Comparison and Benchmarking of Crosstalk Gates -- Practical Realization of Crosstalk Gates -- Poential Applications -- Conclusion and Future Wor

Space station data system analysis/architecture study. Task 2: Options development DR-5. Volume 1: Technology options

The second task in the Space Station Data System (SSDS) Analysis/Architecture Study is the development of an information base that will support the conduct of trade studies and provide sufficient data to make key design/programmatic decisions. This volume identifies the preferred options in the technology category and characterizes these options with respect to performance attributes, constraints, cost, and risk. The technology category includes advanced materials, processes, and techniques that can be used to enhance the implementation of SSDS design structures. The specific areas discussed are mass storage, including space and round on-line storage and off-line storage; man/machine interface; data processing hardware, including flight computers and advanced/fault tolerant computer architectures; and software, including data compression algorithms, on-board high level languages, and software tools. Also discussed are artificial intelligence applications and hard-wire communications

Strategies for neural networks in ballistocardiography with a view towards hardware implementation

A thesis submitted for the degree of Doctor of Philosophy at the University of LutonThe work described in this thesis is based on the results of a clinical trial conducted by the research team at the Medical Informatics Unit of the University of Cambridge, which show that the Ballistocardiogram (BCG) has prognostic value in detecting impaired left ventricular function before it becomes clinically overt as myocardial infarction leading to sudden death. The objective of this study is to develop and demonstrate a framework for realising an on-line BCG signal classification model in a portable device that would have the potential to find pathological signs as early as possible for home health care. Two new on-line automatic BeG classification models for time domain BeG classification are proposed. Both systems are based on a two stage process: input feature extraction followed by a neural classifier. One system uses a principal component analysis neural network, and the other a discrete wavelet transform, to reduce the input dimensionality. Results of the classification, dimensionality reduction, and comparison are presented. It is indicated that the combined wavelet transform and MLP system has a more reliable performance than the combined neural networks system, in situations where the data available to determine the network parameters is limited. Moreover, the wavelet transfonn requires no prior knowledge of the statistical distribution of data samples and the computation complexity and training time are reduced. Overall, a methodology for realising an automatic BeG classification system for a portable instrument is presented. A fully paralJel neural network design for a low cost platform using field programmable gate arrays (Xilinx's XC4000 series) is explored. This addresses the potential speed requirements in the biomedical signal processing field. It also demonstrates a flexible hardware design approach so that an instrument's parameters can be updated as data expands with time. To reduce the hardware design complexity and to increase the system performance, a hybrid learning algorithm using random optimisation and the backpropagation rule is developed to achieve an efficient weight update mechanism in low weight precision learning. The simulation results show that the hybrid learning algorithm is effective in solving the network paralysis problem and the convergence is much faster than by the standard backpropagation rule. The hidden and output layer nodes have been mapped on Xilinx FPGAs with automatic placement and routing tools. The static time analysis results suggests that the proposed network implementation could generate 2.7 billion connections per second performance