Machine Learning in VLSI Computer-Aided Design PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Machine Learning in VLSI Computer-Aided Design PDF full book. Access full book title Machine Learning in VLSI Computer-Aided Design by Ibrahim (Abe) M. Elfadel. Download full books in PDF and EPUB format.
Author: Ibrahim (Abe) M. Elfadel Publisher: Springer ISBN: 3030046664 Category : Technology & Engineering Languages : en Pages : 694
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 : 694
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: ISBN: 9783030046675 Category : Integrated circuits Languages : en Pages :
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
Book Description
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. Illustrate latest techniques for device size and feature optimization. Highlight latest case studies and reviews of the methods used for hardware implementation.
Author: Sandeep Saini Publisher: CRC Press ISBN: 1000523845 Category : Technology & Engineering Languages : en Pages : 292
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: Subarna Shakya Publisher: Springer Nature ISBN: 9811618666 Category : Technology & Engineering Languages : en Pages : 875
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: 1000932443 Category : Technology & Engineering Languages : en Pages : 250
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: Dorothy E. Setliff Publisher: Springer Science & Business Media ISBN: 1461315514 Category : Technology & Engineering Languages : en Pages : 237
Book Description
This book, and the research it describes, resulted from a simple observation we made sometime in 1986. Put simply, we noticed that many VLSI design tools looked "alike". That is, at least at the overall software architecture level, the algorithms and data structures required to solve problem X looked much like those required to solve problem X'. Unfortunately, this resemblance is often of little help in actually writing the software for problem X' given the software for problem X. In the VLSI CAD world, technology changes rapidly enough that design software must continually strive to keep up. And of course, VLSI design software, and engineering design software in general, is often exquisitely sensitive to some aspects of the domain (technology) in which it operates. Modest changes in functionality have an unfortunate tendency to require substantial (and time-consuming) internal software modifications. Now, observing that large engineering software systems are technology dependent is not particularly clever. However, we believe that our approach to xiv Preface dealing with this problem took an interesting new direction. We chose to investigate the extent to which automatic programming ideas cold be used to synthesize such software systems from high-level specifications. This book is one of the results of that effort.
Author: Haoxing Ren Publisher: Springer Nature ISBN: 303113074X Category : Technology & Engineering Languages : en Pages : 585
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: Andrew B. Kahng Publisher: Springer Nature ISBN: 3030964159 Category : Technology & Engineering Languages : en Pages : 329
Book Description
The complexity of modern chip design requires extensive use of specialized software throughout the process. To achieve the best results, a user of this software needs a high-level understanding of the underlying mathematical models and algorithms. In addition, a developer of such software must have a keen understanding of relevant computer science aspects, including algorithmic performance bottlenecks and how various algorithms operate and interact. This book introduces and compares the fundamental algorithms that are used during the IC physical design phase, wherein a geometric chip layout is produced starting from an abstract circuit design. This updated second edition includes recent advancements in the state-of-the-art of physical design, and builds upon foundational coverage of essential and fundamental techniques. Numerous examples and tasks with solutions increase the clarity of presentation and facilitate deeper understanding. A comprehensive set of slides is available on the Internet for each chapter, simplifying use of the book in instructional settings. “This improved, second edition of the book will continue to serve the EDA and design community well. It is a foundational text and reference for the next generation of professionals who will be called on to continue the advancement of our chip design tools and design the most advanced micro-electronics.” Dr. Leon Stok, Vice President, Electronic Design Automation, IBM Systems Group “This is the book I wish I had when I taught EDA in the past, and the one I’m using from now on.” Dr. Louis K. Scheffer, Howard Hughes Medical Institute “I would happily use this book when teaching Physical Design. I know of no other work that’s as comprehensive and up-to-date, with algorithmic focus and clear pseudocode for the key algorithms. The book is beautifully designed!” Prof. John P. Hayes, University of Michigan “The entire field of electronic design automation owes the authors a great debt for providing a single coherent source on physical design that is clear and tutorial in nature, while providing details on key state-of-the-art topics such as timing closure.” Prof. Kurt Keutzer, University of California, Berkeley “An excellent balance of the basics and more advanced concepts, presented by top experts in the field.” Prof. Sachin Sapatnekar, University of Minnesota
Author: Gaynor E. Taylor Publisher: IET ISBN: 9780863412677 Category : Computers Languages : en Pages : 298
Book Description
Samples the present state-of-the-art in CAD for VLSI, covering both newly developed algorithms and applications of techniques from the artificial intelligence community. The material is based on a tutorial course run in conjunction with the 1991 European Conference on Circuit Theory and Design, and should interest engineers involved in the design and testing of integrated circuits and systems. Annotation copyrighted by Book News, Inc., Portland, OR
Author: Ibrahim (Abe) M. Elfadel
Author: Ibrahim (Abe) M. Elfadel
Author: Ibrahim (Abe) M. Elfadel
Author: Sandeep Saini
Author: Sandeep Saini
Author: Subarna Shakya
Author: Ankur Kumar
Author: Dorothy E. Setliff
Author: Haoxing Ren
Author: Andrew B. Kahng
Author: Gaynor E. Taylor