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Author: Ibrahim (Abe) M. Elfadel
Publisher: Springer
ISBN: 3030046664
Category : Technology & Engineering
Languages : en
Pages : 697
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Book Description
This book provides readers with an up-to-date account of the use of machine learning frameworks, methodologies, algorithms and techniques in the context of computer-aided design (CAD) for very-large-scale integrated circuits (VLSI). Coverage includes the various machine learning methods used in lithography, physical design, yield prediction, post-silicon performance analysis, reliability and failure analysis, power and thermal analysis, analog design, logic synthesis, verification, and neuromorphic design. Provides up-to-date information on machine learning in VLSI CAD for device modeling, layout verifications, yield prediction, post-silicon validation, and reliability; Discusses the use of machine learning techniques in the context of analog and digital synthesis; Demonstrates how to formulate VLSI CAD objectives as machine learning problems and provides a comprehensive treatment of their efficient solutions; Discusses the tradeoff between the cost of collecting data and prediction accuracy and provides a methodology for using prior data to reduce cost of data collection in the design, testing and validation of both analog and digital VLSI designs. From the Foreword As the semiconductor industry embraces the rising swell of cognitive systems and edge intelligence, this book could serve as a harbinger and example of the osmosis that will exist between our cognitive structures and methods, on the one hand, and the hardware architectures and technologies that will support them, on the other....As we transition from the computing era to the cognitive one, it behooves us to remember the success story of VLSI CAD and to earnestly seek the help of the invisible hand so that our future cognitive systems are used to design more powerful cognitive systems. This book is very much aligned with this on-going transition from computing to cognition, and it is with deep pleasure that I recommend it to all those who are actively engaged in this exciting transformation. Dr. Ruchir Puri, IBM Fellow, IBM Watson CTO & Chief Architect, IBM T. J. Watson Research Center
Author: Ibrahim (Abe) M. Elfadel
Publisher: Springer
ISBN: 3030046664
Category : Technology & Engineering
Languages : en
Pages : 697
Get Book Here
Book Description
This book provides readers with an up-to-date account of the use of machine learning frameworks, methodologies, algorithms and techniques in the context of computer-aided design (CAD) for very-large-scale integrated circuits (VLSI). Coverage includes the various machine learning methods used in lithography, physical design, yield prediction, post-silicon performance analysis, reliability and failure analysis, power and thermal analysis, analog design, logic synthesis, verification, and neuromorphic design. Provides up-to-date information on machine learning in VLSI CAD for device modeling, layout verifications, yield prediction, post-silicon validation, and reliability; Discusses the use of machine learning techniques in the context of analog and digital synthesis; Demonstrates how to formulate VLSI CAD objectives as machine learning problems and provides a comprehensive treatment of their efficient solutions; Discusses the tradeoff between the cost of collecting data and prediction accuracy and provides a methodology for using prior data to reduce cost of data collection in the design, testing and validation of both analog and digital VLSI designs. From the Foreword As the semiconductor industry embraces the rising swell of cognitive systems and edge intelligence, this book could serve as a harbinger and example of the osmosis that will exist between our cognitive structures and methods, on the one hand, and the hardware architectures and technologies that will support them, on the other....As we transition from the computing era to the cognitive one, it behooves us to remember the success story of VLSI CAD and to earnestly seek the help of the invisible hand so that our future cognitive systems are used to design more powerful cognitive systems. This book is very much aligned with this on-going transition from computing to cognition, and it is with deep pleasure that I recommend it to all those who are actively engaged in this exciting transformation. Dr. Ruchir Puri, IBM Fellow, IBM Watson CTO & Chief Architect, IBM T. J. Watson Research Center
Author: Sandeep Saini
Publisher: CRC Press
ISBN: 1000523810
Category : Technology & Engineering
Languages : en
Pages : 329
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Book Description
Machine learning is a potential solution to resolve bottleneck issues in VLSI via optimizing tasks in the design process. This book aims to provide the latest machine-learning–based methods, algorithms, architectures, and frameworks designed for VLSI design. The focus is on digital, analog, and mixed-signal design techniques, device modeling, physical design, hardware implementation, testability, reconfigurable design, synthesis and verification, and related areas. Chapters include case studies as well as novel research ideas in the given field. Overall, the book provides practical implementations of VLSI design, IC design, and hardware realization using machine learning techniques. Features: Provides the details of state-of-the-art machine learning methods used in VLSI design Discusses hardware implementation and device modeling pertaining to machine learning algorithms Explores machine learning for various VLSI architectures and reconfigurable computing Illustrates the latest techniques for device size and feature optimization Highlights the latest case studies and reviews of the methods used for hardware implementation This book is aimed at researchers, professionals, and graduate students in VLSI, machine learning, electrical and electronic engineering, computer engineering, and hardware systems.
Author: Andrew B. Kahng
Publisher: Springer Science & Business Media
ISBN: 9048195918
Category : Technology & Engineering
Languages : en
Pages : 310
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Book Description
Design and optimization of integrated circuits are essential to the creation of new semiconductor chips, and physical optimizations are becoming more prominent as a result of semiconductor scaling. Modern chip design has become so complex that it is largely performed by specialized software, which is frequently updated to address advances in semiconductor technologies and increased problem complexities. A user of such software needs a high-level understanding of the underlying mathematical models and algorithms. On the other hand, a developer of such software must have a keen understanding of computer science aspects, including algorithmic performance bottlenecks and how various algorithms operate and interact. "VLSI Physical Design: From Graph Partitioning to Timing Closure" introduces and compares algorithms that are used during the physical design phase of integrated-circuit design, wherein a geometric chip layout is produced starting from an abstract circuit design. The emphasis is on essential and fundamental techniques, ranging from hypergraph partitioning and circuit placement to timing closure.
Author: Wolfgang Fichtner
Publisher: Springer Science & Business Media
ISBN: 1461319854
Category : Technology & Engineering
Languages : en
Pages : 555
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Book Description
The summer school on VLSf GAD Tools and Applications was held from July 21 through August 1, 1986 at Beatenberg in the beautiful Bernese Oberland in Switzerland. The meeting was given under the auspices of IFIP WG 10. 6 VLSI, and it was sponsored by the Swiss Federal Institute of Technology Zurich, Switzerland. Eighty-one professionals were invited to participate in the summer school, including 18 lecturers. The 81 participants came from the following countries: Australia (1), Denmark (1), Federal Republic of Germany (12), France (3), Italy (4), Norway (1), South Korea (1), Sweden (5), United Kingdom (1), United States of America (13), and Switzerland (39). Our goal in the planning for the summer school was to introduce the audience into the realities of CAD tools and their applications to VLSI design. This book contains articles by all 18 invited speakers that lectured at the summer school. The reader should realize that it was not intended to publish a textbook. However, the chapters in this book are more or less self-contained treatments of the particular subjects. Chapters 1 and 2 give a broad introduction to VLSI Design. Simulation tools and their algorithmic foundations are treated in Chapters 3 to 5 and 17. Chapters 6 to 9 provide an excellent treatment of modern layout tools. The use of CAD tools and trends in the design of 32-bit microprocessors are the topics of Chapters 10 through 16. Important aspects in VLSI testing and testing strategies are given in Chapters 18 and 19.
Author: Subarna Shakya
Publisher: Springer Nature
ISBN: 9811618666
Category : Technology & Engineering
Languages : en
Pages : 875
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Book Description
This book gathers selected high-quality research papers presented at International Conference on Mobile Computing and Sustainable Informatics (ICMCSI 2021) organized by Pulchowk Campus, Institute of Engineering, Tribhuvan University, Nepal, during 29–30 January 2021. The book discusses recent developments in mobile communication technologies ranging from mobile edge computing devices, to personalized, embedded and sustainable applications. The book covers vital topics like mobile networks, computing models, algorithms, sustainable models and advanced informatics that supports the symbiosis of mobile computing and sustainable informatics.
Author: Ankur Kumar
Publisher: CRC Press
ISBN: 1000932346
Category : Technology & Engineering
Languages : en
Pages : 218
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Book Description
The text comprehensively discusses the latest Opto-VLSI devices and circuits useful for healthcare and biomedical applications. It further emphasizes the importance of smart technologies such as artificial intelligence, machine learning, and the internet of things for the biomedical and healthcare industries. Discusses advanced concepts in the field of electro-optics devices for medical applications. Presents optimization techniques including logical effort, particle swarm optimization and genetic algorithm to design Opto-VLSI devices and circuits. Showcases the concepts of artificial intelligence and machine learning for smart medical devices and data auto-collection for distance treatment. Covers advanced Opto-VLSI devices including a field-effect transistor and optical sensors, spintronic and photonic devices. Highlights application of flexible electronics in health monitoring and artificial intelligence integration for better medical devices. The text presents the advances in the fields of optics and VLSI and their applicability in diverse areas including biomedical engineering and the healthcare sector. It covers important topics such as FET biosensors, optical biosensors and advanced optical materials. It further showcases the significance of smart technologies such as artificial intelligence, machine learning and the internet of things for the biomedical and healthcare industries. It will serve as an ideal design book for senior undergraduate, graduate students, and academic researchers in the fields including electrical engineering, electronics and communication engineering, computer engineering and biomedical engineering.
Author: Haoxing Ren
Publisher: Springer Nature
ISBN: 303113074X
Category : Technology & Engineering
Languages : en
Pages : 585
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Book Description
This book serves as a single-source reference to key machine learning (ML) applications and methods in digital and analog design and verification. Experts from academia and industry cover a wide range of the latest research on ML applications in electronic design automation (EDA), including analysis and optimization of digital design, analysis and optimization of analog design, as well as functional verification, FPGA and system level designs, design for manufacturing (DFM), and design space exploration. The authors also cover key ML methods such as classical ML, deep learning models such as convolutional neural networks (CNNs), graph neural networks (GNNs), generative adversarial networks (GANs) and optimization methods such as reinforcement learning (RL) and Bayesian optimization (BO). All of these topics are valuable to chip designers and EDA developers and researchers working in digital and analog designs and verification.
Author: Andrea Calimera
Publisher: Springer Nature
ISBN: 3030816419
Category : Computers
Languages : en
Pages : 372
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Book Description
This book contains extended and revised versions of the best papers presented at the 28th IFIP WG 10.5/IEEE International Conference on Very Large Scale Integration, VLSI-SoC 2020, held in Salt Lake City, UT, USA, in October 2020.* The 16 full papers included in this volume were carefully reviewed and selected from the 38 papers (out of 74 submissions) presented at the conference. The papers discuss the latest academic and industrial results and developments as well as future trends in the field of System-on-Chip (SoC) design, considering the challenges of nano-scale, state-of-the-art and emerging manufacturing technologies. In particular they address cutting-edge research fields like low-power design of RF, analog and mixed-signal circuits, EDA tools for the synthesis and verification of heterogenous SoCs, accelerators for cryptography and deep learning and on-chip Interconnection system, reliability and testing, and integration of 3D-ICs. *The conference was held virtually.
Author: Timon Rabczuk
Publisher: Springer Nature
ISBN: 3031366441
Category : Technology & Engineering
Languages : en
Pages : 456
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Book Description
Machine learning (ML) approaches have been extensively and successfully employed in various areas, like in economics, medical predictions, face recognition, credit card fraud detection, and spam filtering. There is clearly also the potential that ML techniques developed in Engineering and the Sciences will drastically increase the possibilities of analysis and accelerate the design to analysis time. With the use of ML techniques, coupled to conventional methods like finite element and digital twin technologies, new avenues of modeling and simulation can be opened but the potential of these ML techniques needs to still be fully harvested, with the methods developed and enhanced. The objective of this book is to provide an overview of ML in Engineering and the Sciences presenting fundamental theoretical ingredients with a focus on the next generation of computer modeling in Engineering and the Sciences in which the exciting aspects of machine learning are incorporated. The book is of value to any researcher and practitioner interested in research or applications of ML in the areas of scientific modeling and computer aided engineering.
Author: Jose G. Delgado-Frias
Publisher: Springer Science & Business Media
ISBN: 1461537525
Category : Computers
Languages : en
Pages : 411
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Book Description
This book is an edited selection of the papers presented at the International Workshop on VLSI for Artifidal Intelligence and Neural Networks which was held at the University of Oxford in September 1990. Our thanks go to all the contributors and especially to the programme committee for all their hard work. Thanks are also due to the ACM-SIGARCH, the IEEE Computer Society, and the lEE for publicizing the event and to the University of Oxford and SUNY-Binghamton for their active support. We are particularly grateful to Anna Morris, Maureen Doherty and Laura Duffy for coping with the administrative problems. Jose Delgado-Frias Will Moore April 1991 vii PROLOGUE Artificial intelligence and neural network algorithms/computing have increased in complexity as well as in the number of applications. This in tum has posed a tremendous need for a larger computational power than can be provided by conventional scalar processors which are oriented towards numeric and data manipulations. Due to the artificial intelligence requirements (symbolic manipulation, knowledge representation, non-deterministic computations and dynamic resource allocation) and neural network computing approach (non-programming and learning), a different set of constraints and demands are imposed on the computer architectures for these applications.
