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Books > Computing & IT > Computer hardware & operating systems > Computer architecture & logic design
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Machine Learning in VLSI Computer-Aided Design (Hardcover, 1st ed. 2019)
Loot Price: R5,008
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Machine Learning in VLSI Computer-Aided Design (Hardcover, 1st ed. 2019)
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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
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