2017 IEEE 26th Asian Test Symposium
Author:
Publisher:
Published: 2017
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ISBN-13: 9781538624371
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VLSI Design and Test
Author: S. Rajaram
Publisher: Springer
Published: 2019-01-24
Total Pages: 728
ISBN-13: 9811359504
DOWNLOAD EBOOKThis book constitutes the refereed proceedings of the 22st International Symposium on VLSI Design and Test, VDAT 2018, held in Madurai, India, in June 2018. The 39 full papers and 11 short papers presented together with 8 poster papers were carefully reviewed and selected from 231 submissions. The papers are organized in topical sections named: digital design; analog and mixed signal design; hardware security; micro bio-fluidics; VLSI testing; analog circuits and devices; network-on-chip; memory; quantum computing and NoC; sensors and interfaces.
Machine Learning Techniques for VLSI Chip Design
Author: Abhishek Kumar
Publisher: John Wiley & Sons
Published: 2023-06-26
Total Pages: 244
ISBN-13: 1119910471
DOWNLOAD EBOOKMACHINE LEARNING TECHNIQUES FOR VLSI CHIP DESIGN This cutting-edge new volume covers the hardware architecture implementation, the software implementation approach, the efficient hardware of machine learning applications with FPGA or CMOS circuits, and many other aspects and applications of machine learning techniques for VLSI chip design. Artificial intelligence (AI) and machine learning (ML) have, or will have, an impact on almost every aspect of our lives and every device that we own. AI has benefitted every industry in terms of computational speeds, accurate decision prediction, efficient machine learning (ML), and deep learning (DL) algorithms. The VLSI industry uses the electronic design automation tool (EDA), and the integration with ML helps in reducing design time and cost of production. Finding defects, bugs, and hardware Trojans in the design with ML or DL can save losses during production. Constraints to ML-DL arise when having to deal with a large set of training datasets. This book covers the learning algorithm for floor planning, routing, mask fabrication, and implementation of the computational architecture for ML-DL. The future aspect of the ML-DL algorithm is to be available in the format of an integrated circuit (IC). A user can upgrade to the new algorithm by replacing an IC. This new book mainly deals with the adaption of computation blocks like hardware accelerators and novel nano-material for them based upon their application and to create a smart solution. This exciting new volume is an invaluable reference for beginners as well as engineers, scientists, researchers, and other professionals working in the area of VLSI architecture development.
ISTFA 2017: Proceedings from the 43rd International Symposium for Testing and Failure Analysis
Author: ASM International
Publisher: ASM International
Published: 2017-12-01
Total Pages: 666
ISBN-13: 1627081518
DOWNLOAD EBOOKThe theme for the November 2017 conference was Striving for 100% Success Rate. Papers focus on the tools and techniques needed for maximizing the success rate in every aspect of the electronic device failure analysis process.
VLSI and Hardware Implementations using Modern Machine Learning Methods
Author: Sandeep Saini
Publisher: CRC Press
Published: 2021-12-31
Total Pages: 292
ISBN-13: 1000523845
DOWNLOAD EBOOKMachine 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.
Machine Learning in VLSI Computer-Aided Design
Author: Ibrahim (Abe) M. Elfadel
Publisher: Springer
Published: 2019-03-15
Total Pages: 697
ISBN-13: 3030046664
DOWNLOAD EBOOKThis 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
NANO-CHIPS 2030
Author: Boris Murmann
Publisher: Springer Nature
Published: 2020-06-08
Total Pages: 597
ISBN-13: 3030183386
DOWNLOAD EBOOKIn this book, a global team of experts from academia, research institutes and industry presents their vision on how new nano-chip architectures will enable the performance and energy efficiency needed for AI-driven advancements in autonomous mobility, healthcare, and man-machine cooperation. Recent reviews of the status quo, as presented in CHIPS 2020 (Springer), have prompted the need for an urgent reassessment of opportunities in nanoelectronic information technology. As such, this book explores the foundations of a new era in nanoelectronics that will drive progress in intelligent chip systems for energy-efficient information technology, on-chip deep learning for data analytics, and quantum computing. Given its scope, this book provides a timely compendium that hopes to inspire and shape the future of nanoelectronics in the decades to come.
Sensors Fault Diagnosis Trends and Applications
Author: Piotr Witczak
Publisher: MDPI
Published: 2021-09-01
Total Pages: 236
ISBN-13: 3036510486
DOWNLOAD EBOOKFault diagnosis has always been a concern for industry. In general, diagnosis in complex systems requires the acquisition of information from sensors and the processing and extracting of required features for the classification or identification of faults. Therefore, fault diagnosis of sensors is clearly important as faulty information from a sensor may lead to misleading conclusions about the whole system. As engineering systems grow in size and complexity, it becomes more and more important to diagnose faulty behavior before it can lead to total failure. In the light of above issues, this book is dedicated to trends and applications in modern-sensor fault diagnosis.
VLSI Design and Test
Author: Ambika Prasad Shah
Publisher: Springer Nature
Published: 2022-12-16
Total Pages: 607
ISBN-13: 3031215141
DOWNLOAD EBOOKThis book constitutes the proceedings of the 26th International Symposium on VLSI Design and Test, VDAT 2022, which took place in Jammu, India, in July 2022. The 32 regular papers and 16 short papers presented in this volume were carefully reviewed and selected from 220 submissions. They were organized in topical sections as follows: Devices and Technology; Sensors; Analog/Mixed Signal; Digital Design; Emerging Technologies and Memory; System Design.
Advances in Swarm Intelligence
Author: Ying Tan
Publisher: Springer Nature
Published: 2023-07-07
Total Pages: 502
ISBN-13: 3031366220
DOWNLOAD EBOOKThis two-volume set LNCS 13968 and 13969 constitutes the proceedings of the 14th International Conference on Advances in Swarm Intelligence, ICSI 2023, which took place in Shenzhen, China, China, in July 2023. The theme of this year’s conference was “Serving Life with Swarm Intelligence”. The 81 full papers presented were carefully reviewed and selected from 170 submissions. The papers are organized into 12 cohesive sections covering major topics of swarm intelligence research and its development and applications. The papers of the first part cover topics such as: Swarm Intelligence Computing; Swarm Intelligence Optimization Algorithms; Particle Swarm Optimization Algorithms; Genetic Algorithms; Optimization Computing Algorithms; Neural Network Search & Large-Scale Optimization; Multi-objective Optimization.
