Artificial Intelligence for Testing VLSI Circuits PDF Download
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Author: Reza Raeisi
Publisher:
ISBN:
Category :
Languages : en
Pages : 326
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Book Description
Author: Reza Raeisi
Publisher:
ISBN:
Category :
Languages : en
Pages : 326
Get Book Here
Book Description
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: Gaynor E. Taylor
Publisher: IET
ISBN: 9780863412677
Category : Computers
Languages : en
Pages : 298
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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: Nikolas G Bourbakis
Publisher: World Scientific
ISBN: 981449903X
Category : Computers
Languages : en
Pages : 545
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Book Description
Contents:A New Way to Acquire Knowledge (H-Y Wang)An SPN Knowledge Representation Scheme (J Gattiker & N Bourbakis)On the Deep Structures of Word Problems and Their Construction (F Gomez)Resolving Conflicts in Inheritance Reasoning with Statistical Approach (C W Lee)Integrating High and Low Level Computer Vision for Scene Understanding (R Malik & S So)The Evolution of Commercial AI Tools: The First Decade (F Hayes-Roth)Reengineering: The AI Generation — Billions on the Table (J S Minor Jr)An Intelligent Tool for Discovering Data Dependencies in Relational DBS (P Gavaskar & F Golshani)A Case-Based Reasoning (CBR) Tool to Assist Traffic Flow (B Das & S Bayles)A Study of Financial Expert System Based on Flops (T Kaneko & K Takenaka)An Associative Data Parallel Compilation Model for Tight Integration of High Performance Knowledge Retrieval and Computation (A K Bansal)Software Automation: From Silly to Intelligent (J-F Xu et al.)Software Engineering Using Artificial Intelligence: The Knowledge Based Software Assistant (D White)Knowledge Based Derivation of Programs from Specifications (T Weight et al.)Automatic Functional Model Generation for Parallel Fault Design Error Simulations (S-E Chang & S A Szygenda)Visual Reverse Engineering Using SPNs for Automated Diagnosis and Functional Simulation of Digital Circuits (J Gattiker & S Mertoguno)The Impact of AI in VLSI Design Automation (M Mortazavi & N Bourbakis)The Automated Acquisition of Subcategorizations of Verbs, Nouns and Adjectives from Sample Sentences (F Gomez)General Method for Planning and Rendezvous Problems (K I Trovato)Learning to Improve Path Planning Performance (P C Chen)Incremental Adaptation as a Method to Improve Reactive Behavior (A J Hendriks & D M Lyons)An SPN-Neural Planning Methodology for Coordination of Multiple Robotic Arms with Constrained Placement (N Bourbakis & A Tascillo) Readership: Computer scientists, artificial intelligence practitioners and robotics users. keywords:
Author: Ibrahim (Abe) M. Elfadel
Publisher: Springer
ISBN: 3030046664
Category : Technology & Engineering
Languages : en
Pages : 694
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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: Balwinder Raj
Publisher: John Wiley & Sons
ISBN: 1394204353
Category : Technology & Engineering
Languages : en
Pages : 388
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Book Description
With its in-depth exploration of the close connection between microelectronics, AI, and VLSI technology, this book offers valuable insights into the cutting-edge techniques and tools used in VLSI design automation, making it an essential resource for anyone seeking to stay ahead in the rapidly evolving field of VLSI design. Very large-scale integration (VLSI) is the inter-disciplinary science of utilizing advanced semiconductor technology to create various functions of computer system. This book addresses the close link of microelectronics and artificial intelligence (AI). By combining VLSI technology, a very powerful computer architecture confinement is possible. To overcome problems at different design stages, researchers introduced artificial intelligent (AI) techniques in VLSI design automation. AI techniques, such as knowledge-based and expert systems, first try to define the problem and then choose the best solution from the domain of possible solutions. These days, several CAD technologies, such as Synopsys and Mentor Graphics, are specifically created to increase the automation of VLSI design. When a task is completed using the appropriate tool, each stage of the task design produces outcomes that are more productive than typical. However, combining all of these tools into a single package offer has drawbacks. We can’t really use every outlook without sacrificing the efficiency and usefulness of our output. The researchers decided to include AI approaches into VLSI design automation in order to get around these obstacles. AI is one of the fastest growing tools in the world of technology and innovation that helps to make computers more reliable and easy to use. Artificial Intelligence in VLSI design has provided high-end and more feasible solutions to the difficulties faced by the VLSI industry. Physical design, RTL design, STA, etc. are some of the most in-demand courses to enter the VLSI industry. These courses help develop a better understanding of the many tools like Synopsis. With each new dawn, artificial intelligence in VLSI design is continually evolving, and new opportunities are being investigated.
Author: Sandeep Saini
Publisher: CRC Press
ISBN: 1000523845
Category : Technology & Engineering
Languages : en
Pages : 292
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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: Wei Zeng
Publisher:
ISBN:
Category :
Languages : en
Pages : 95
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Book Description
With the advance of Very Large Scale Integration (VLSI) technology, the design process of VLSI circuits becomes more complex, challenging, and time-consuming. Recent years have seen a rising trend of machine learning (ML) incorporated in VLSI design flow for better and more efficient design and implementation of integrated circuits. Explainable Artificial Intelligence (XAI) is an emerging technique that aims to perform prediction tasks while providing explanations for the predictions. XAI adds transparency and trustworthiness to ML models, leading to better human understanding and exploitation of the models. With ML being applied in VLSI design, it is desirable to adopt ideas from XAI for even better and more trustworthy outcomes of VLSI design. This dissertation explores the usage of Shapley Additive Explanation (SHAP)--a recent development in XAI, on different aspects and stages of VLSI design flow. Specifically, we propose three techniques that adopt SHAP in front-end and back-end design flows, including (a) SHAP-guided layout obfuscation for enhanced hardware security in split manufacturing, (b) explainable routability prediction, which accelerates the physical design flow and provides hints for improving the design, and (c) explainable-ML-guided approximate logic synthesis for area-efficient computing in error-tolerant applications. These are the first works that incorporate XAI into VLSI design methodology. All of them achieve better results than their conventional counterparts or existing works in similar settings.
Author: Narinder Singh
Publisher: Springer Science & Business Media
ISBN: 146131979X
Category : Technology & Engineering
Languages : en
Pages : 202
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Book Description
I am indebted to my thesis advisor, Michael Genesereth, for his guidance, inspiration, and support which has made this research possible. As a teacher and a sounding board for new ideas, Mike was extremely helpful in pointing out Haws, and suggesting new directions to explore. I would also like to thank Harold Brown for introducing me to the application of artificial intelligence to reasoning about designs, and his many valuable comments as a reader of this thesis. Significant contribu tions by the other members of my reading committee, Mark Horowitz, and Allen Peterson have greatly improved the content and organization of this thesis by forcing me to communicate my ideas more clearly. I am extremely grateful to the other members of the Logic Group at the Heuristic Programming Project for being a sounding board for my ideas, and providing useful comments. In particular, I would like to thank Matt Ginsberg, Vineet Singh, Devika Subramanian, Richard Trietel, Dave Smith, Jock Mackinlay, and Glenn Kramer for their pointed criticisms. This research was supported by Schlumberger Palo Alto Research (previously Fairchild Laboratory for Artificial Intelligence). I am grateful to Peter Hart, the former head of the AI lab, and his successor Marty Tenenbaum for providing an excellent environment for performing this research.
Author: Biswajit Mishra
Publisher: Springer Nature
ISBN: 9811669406
Category : Computers
Languages : en
Pages : 167
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Book Description
This book highlights selected papers presented at the 10th International Symposium on Embedded Computing and System Design (ISED) 2021. This symposium provides a platform for researchers to share the latest scientific achievements of embedded computing and system design. The book is divided into three broad sections. The first section discusses topics like VLSI and testing, circuits and systems with a focus on emerging technologies. The second section discusses topics like embedded hardware and software systems and novel applications. The final section discusses the state-of-the-art technologies involving IoT, artificial intelligence, green and edge computing that demonstrates the issues currently.
