[PDF] Machine Learning in VLSI Computer-Aided Design By Ibrahim (Abe) M. Elfadel, Duane S. Boning and Xin Li Free Download


[PDF] Download Ibrahim (Abe) M. Elfadel, Duane S. Boning and Xin Li by Machine Learning in VLSI Computer-Aided Design

Machine Learning in VLSI Computer-Aided Design written by Ibrahim (Abe) M. Elfadel, Duane S. Boning and Xin Li is very useful for Mechanical Engineering (MECH) students and also who are all having an interest to develop their knowledge in the field of Design, Automobile, Production, Thermal Engineering as well as all the works related to Mechanical field. This Book provides an clear examples on each and every topics covered in the contents of the book to provide an every user those who are read to develop their knowledge.

Machine Learning in VLSI Computer-Aided Design written to meet exhaustively the requirements of various syllabus in the subject of the courses in B.E /B.Tech/ B.Sc (Engineering) of various Indian Universities. It is Equally suitable for UPSC, AIME and all other competitive examinations in the field of Engineering.

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Machine Learning in VLSI Computer-Aided Design By Ibrahim (Abe) M. Elfadel, Duane S. Boning and Xin Li – PDF Free Download Machine Learning in VLSI Computer-Aided Design By Ibrahim (Abe)
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Description of a Book

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.

  1. Provides up-to-date information on machine learning in VLSI CAD for device modeling, layout verification, yield prediction, post-silicon validation, and reliability;
  2. Discusses the use of machine learning techniques in the context of analog and digital synthesis;
  3. Demonstrates how to formulate VLSI CAD objectives as machine learning problems and provides a comprehensive treatment of their efficient solutions;
  4. 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.

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 be hooves 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

About Author

Ibrahim (Abe) M. Elfadel, Duane S. Boning and Xin Li

Book Details

Machine Learning in VLSI Computer-Aided Design written by Ibrahim (Abe) M. Elfadel, Duane S. Boning and Xin Li detailed in the below table…

Name of the Book Machine Learning in VLSI Computer-Aided Design
Name of the Author(s) Ibrahim (Abe) M. Elfadel, Duane S. Boning and Xin Li
Language English

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