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Extreme Statistics in Nanoscale Memory Design

2010-09-09 Technology & Engineering
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Release : 2010-09-09
Genre : Technology & Engineering
Kind : eBook
Book Rating : 064/5 ( reviews)

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Book Synopsis Extreme Statistics in Nanoscale Memory Design by : Amith Singhee

Download or read book Extreme Statistics in Nanoscale Memory Design written by Amith Singhee. This book was released on 2010-09-09. Available in PDF, EPUB and Kindle. Book excerpt: Knowledge exists: you only have to ?nd it VLSI design has come to an important in?ection point with the appearance of large manufacturing variations as semiconductor technology has moved to 45 nm feature sizes and below. If we ignore the random variations in the manufacturing process, simulation-based design essentially becomes useless, since its predictions will be far from the reality of manufactured ICs. On the other hand, using design margins based on some traditional notion of worst-case scenarios can force us to sacri?ce too much in terms of power consumption or manufacturing cost, to the extent of making the design goals even infeasible. We absolutely need to explicitly account for the statistics of this random variability, to have design margins that are accurate so that we can ?nd the optimum balance between yield loss and design cost. This discontinuity in design processes has led many researchers to develop effective methods of statistical design, where the designer can simulate not just the behavior of the nominal design, but the expected statistics of the behavior in manufactured ICs. Memory circuits tend to be the hardest hit by the problem of these random variations because of their high replication count on any single chip, which demands a very high statistical quality from the product. Requirements of 5–6s (0.

Extreme Statistics in Nanoscale Memory Design

2010-09-17 Technology & Engineering
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Release : 2010-09-17
Genre : Technology & Engineering
Kind : eBook
Book Rating : 056/5 ( reviews)

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Book Synopsis Extreme Statistics in Nanoscale Memory Design by : Amith Singhee

Download or read book Extreme Statistics in Nanoscale Memory Design written by Amith Singhee. This book was released on 2010-09-17. Available in PDF, EPUB and Kindle. Book excerpt: Knowledge exists: you only have to ?nd it VLSI design has come to an important in?ection point with the appearance of large manufacturing variations as semiconductor technology has moved to 45 nm feature sizes and below. If we ignore the random variations in the manufacturing process, simulation-based design essentially becomes useless, since its predictions will be far from the reality of manufactured ICs. On the other hand, using design margins based on some traditional notion of worst-case scenarios can force us to sacri?ce too much in terms of power consumption or manufacturing cost, to the extent of making the design goals even infeasible. We absolutely need to explicitly account for the statistics of this random variability, to have design margins that are accurate so that we can ?nd the optimum balance between yield loss and design cost. This discontinuity in design processes has led many researchers to develop effective methods of statistical design, where the designer can simulate not just the behavior of the nominal design, but the expected statistics of the behavior in manufactured ICs. Memory circuits tend to be the hardest hit by the problem of these random variations because of their high replication count on any single chip, which demands a very high statistical quality from the product. Requirements of 5–6s (0.

Machine Learning in VLSI Computer-Aided Design

2019-03-15 Technology & Engineering
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Release : 2019-03-15
Genre : Technology & Engineering
Kind : eBook
Book Rating : 664/5 ( reviews)

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Book Synopsis Machine Learning in VLSI Computer-Aided Design by : Ibrahim (Abe) M. Elfadel

Download or read book Machine Learning in VLSI Computer-Aided Design written by Ibrahim (Abe) M. Elfadel. This book was released on 2019-03-15. Available in PDF, EPUB and Kindle. Book excerpt: 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

Green Computing with Emerging Memory

2012-09-26 Technology & Engineering
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Release : 2012-09-26
Genre : Technology & Engineering
Kind : eBook
Book Rating : 121/5 ( reviews)

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Book Synopsis Green Computing with Emerging Memory by : Takayuki Kawahara

Download or read book Green Computing with Emerging Memory written by Takayuki Kawahara. This book was released on 2012-09-26. Available in PDF, EPUB and Kindle. Book excerpt: This book describes computing innovation, using non-volatile memory for a sustainable world. It appeals to both computing engineers and device engineers by describing a new means of lower power computing innovation, without sacrificing performance over conventional low-voltage operation. Readers will be introduced to methods of design and implementation for non-volatile memory which allow computing equipment to be turned off normally when not in use and to be turned on instantly to operate with full performance when needed.

Evolvable Hardware

2015-09-14 Computers
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Release : 2015-09-14
Genre : Computers
Kind : eBook
Book Rating : 162/5 ( reviews)

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Book Synopsis Evolvable Hardware by : Martin A. Trefzer

Download or read book Evolvable Hardware written by Martin A. Trefzer. This book was released on 2015-09-14. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the basic theory, practical details and advanced research of the implementation of evolutionary methods on physical substrates. Most of the examples are from electronic engineering applications, including transistor-level design and system-level implementation. The authors present an overview of the successes achieved, and the book will act as a point of reference for both academic and industrial researchers.

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