Machine Learning Applications in Electronic Design Automation

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Author :
Publisher : Springer Nature
ISBN 13 : 303113074X
Total Pages : 585 pages
Book Rating : 4.48/5 ( download)

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Book Synopsis Machine Learning Applications in Electronic Design Automation by : Haoxing Ren

Download or read book Machine Learning Applications in Electronic Design Automation written by Haoxing Ren and published by Springer Nature. This book was released on 2023-01-01 with total page 585 pages. Available in PDF, EPUB and Kindle. Book excerpt: ​This book serves as a single-source reference to key machine learning (ML) applications and methods in digital and analog design and verification. Experts from academia and industry cover a wide range of the latest research on ML applications in electronic design automation (EDA), including analysis and optimization of digital design, analysis and optimization of analog design, as well as functional verification, FPGA and system level designs, design for manufacturing (DFM), and design space exploration. The authors also cover key ML methods such as classical ML, deep learning models such as convolutional neural networks (CNNs), graph neural networks (GNNs), generative adversarial networks (GANs) and optimization methods such as reinforcement learning (RL) and Bayesian optimization (BO). All of these topics are valuable to chip designers and EDA developers and researchers working in digital and analog designs and verification.

Machine Intelligence in Design Automation

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Publisher :
ISBN 13 : 9781980554356
Total Pages : 219 pages
Book Rating : 4.58/5 ( download)

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Book Synopsis Machine Intelligence in Design Automation by : Rohit Sharma

Download or read book Machine Intelligence in Design Automation written by Rohit Sharma and published by . This book was released on 2018-03-13 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a hands-on approach for solving electronic design automation problems with modern machine intelligence techniques by including step-by-step development of commercial grade design applications including resistance estimation, capacitance estimation, cell classification and others using dataset extracted from designs at 20nm. It walks the reader step by step in building solution flow for EDA problems with Python and Tensorflow.Intended audience includes design automation engineers, managers, executives, research professionals, graduate students, Machine learning enthusiasts, EDA and CAD developers, mentors, and the merely inquisitive. It is organized to serve as a compendium to a beginner, a ready reference to intermediate and source for an expert.

Machine Learning in VLSI Computer-Aided Design

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Publisher : Springer
ISBN 13 : 3030046664
Total Pages : 694 pages
Book Rating : 4.68/5 ( download)

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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 and published by Springer. This book was released on 2019-03-15 with total page 694 pages. 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

Machine Learning Techniques for VLSI Chip Design

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Publisher : John Wiley & Sons
ISBN 13 : 1119910471
Total Pages : 244 pages
Book Rating : 4.73/5 ( download)

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Book Synopsis Machine Learning Techniques for VLSI Chip Design by : Abhishek Kumar

Download or read book Machine Learning Techniques for VLSI Chip Design written by Abhishek Kumar and published by John Wiley & Sons. This book was released on 2023-06-26 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: MACHINE 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.

Using Artificial Neural Networks for Analog Integrated Circuit Design Automation

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Publisher : Springer Nature
ISBN 13 : 3030357430
Total Pages : 117 pages
Book Rating : 4.36/5 ( download)

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Book Synopsis Using Artificial Neural Networks for Analog Integrated Circuit Design Automation by : João P. S. Rosa

Download or read book Using Artificial Neural Networks for Analog Integrated Circuit Design Automation written by João P. S. Rosa and published by Springer Nature. This book was released on 2019-12-11 with total page 117 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses the automatic sizing and layout of analog integrated circuits (ICs) using deep learning (DL) and artificial neural networks (ANN). It explores an innovative approach to automatic circuit sizing where ANNs learn patterns from previously optimized design solutions. In opposition to classical optimization-based sizing strategies, where computational intelligence techniques are used to iterate over the map from devices’ sizes to circuits’ performances provided by design equations or circuit simulations, ANNs are shown to be capable of solving analog IC sizing as a direct map from specifications to the devices’ sizes. Two separate ANN architectures are proposed: a Regression-only model and a Classification and Regression model. The goal of the Regression-only model is to learn design patterns from the studied circuits, using circuit’s performances as input features and devices’ sizes as target outputs. This model can size a circuit given its specifications for a single topology. The Classification and Regression model has the same capabilities of the previous model, but it can also select the most appropriate circuit topology and its respective sizing given the target specification. The proposed methodology was implemented and tested on two analog circuit topologies.

2022 27th Asia and South Pacific Design Automation Conference (ASP-DAC).

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Publisher :
ISBN 13 : 9781665421355
Total Pages : pages
Book Rating : 4.55/5 ( download)

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Book Synopsis 2022 27th Asia and South Pacific Design Automation Conference (ASP-DAC). by :

Download or read book 2022 27th Asia and South Pacific Design Automation Conference (ASP-DAC). written by and published by . This book was released on 2022 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Essential Electronic Design Automation (EDA)

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Publisher : Prentice Hall Professional
ISBN 13 : 9780131828292
Total Pages : 256 pages
Book Rating : 4.90/5 ( download)

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Book Synopsis Essential Electronic Design Automation (EDA) by : Mark Birnbaum

Download or read book Essential Electronic Design Automation (EDA) written by Mark Birnbaum and published by Prentice Hall Professional. This book was released on 2004 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: & Describes the engineering needs addressed by the individual EDA tools and covers EDA from both the provider and user viewpoints. & & Learn the importance of marketing and business trends in the EDA industry. & & The EDA consortium is made up of major corporations including SUN, HP, and Intel.

Modern Approaches in Machine Learning and Cognitive Science: A Walkthrough

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Publisher : Springer Nature
ISBN 13 : 3031430093
Total Pages : 337 pages
Book Rating : 4.91/5 ( download)

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Book Synopsis Modern Approaches in Machine Learning and Cognitive Science: A Walkthrough by : Vinit Kumar Gunjan

Download or read book Modern Approaches in Machine Learning and Cognitive Science: A Walkthrough written by Vinit Kumar Gunjan and published by Springer Nature. This book was released on 2024-01-13 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a systematic and comprehensive overview of cognitive intelligence and AI-enabled IoT ecosystem and machine learning, capable of recognizing the object pattern in complex and large data sets. A remarkable success has been experienced in the last decade by emulating the brain–computer interface. It presents the applied cognitive science methods and AI-enabled technologies that have played a vital role at the core of practical solutions for a wide scope of tasks between handheld apps and industrial process control, autonomous vehicles, IoT, intelligent learning environment, game theory, human computer interaction, environmental policies, life sciences, playing computer games, computational theory, and engineering development. The book contains contents highlighting artificial neural networks that are analogous to the networks of neurons that comprise the brain and have given computers the ability to distinguish an image of a cat from one of a coconut, to spot pedestrians with enough accuracy to direct a self-driving car, and to recognize and respond to the spoken word. The chapters in this book focus on audiences interested in artificial intelligence, machine learning, fuzzy, cognitive and neurofuzzy-inspired computational systems, their theories, mechanisms, and architecture, which underline human and animal behavior, and their application to conscious and intelligent systems. In the current version, it focuses on the successful implementation and step-by-step execution and explanation of practical applications of the domain. It also offers a wide range of inspiring and interesting cutting-edge contributions on applications of machine learning, artificial intelligence, and cognitive science such as healthcare products, AI-enabled IoT, gaming, medical, and engineering. Overall, this book provides valuable information on effective, cutting-edge techniques, and approaches for students, researchers, practitioners, and academics in the field of machine learning and cognitive science. Furthermore, the purpose of this book is to address the interests of a broad spectrum of practitioners, students, and researchers, who are interested in applying machine learning and cognitive science methods in their respective domains.

Opto-VLSI Devices and Circuits for Biomedical and Healthcare Applications

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Author :
Publisher : CRC Press
ISBN 13 : 1000932346
Total Pages : 218 pages
Book Rating : 4.48/5 ( download)

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Book Synopsis Opto-VLSI Devices and Circuits for Biomedical and Healthcare Applications by : Ankur Kumar

Download or read book Opto-VLSI Devices and Circuits for Biomedical and Healthcare Applications written by Ankur Kumar and published by CRC Press. This book was released on 2023-09-04 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: The text comprehensively discusses the latest Opto-VLSI devices and circuits useful for healthcare and biomedical applications. It further emphasizes the importance of smart technologies such as artificial intelligence, machine learning, and the internet of things for the biomedical and healthcare industries. Discusses advanced concepts in the field of electro-optics devices for medical applications. Presents optimization techniques including logical effort, particle swarm optimization and genetic algorithm to design Opto-VLSI devices and circuits. Showcases the concepts of artificial intelligence and machine learning for smart medical devices and data auto-collection for distance treatment. Covers advanced Opto-VLSI devices including a field-effect transistor and optical sensors, spintronic and photonic devices. Highlights application of flexible electronics in health monitoring and artificial intelligence integration for better medical devices. The text presents the advances in the fields of optics and VLSI and their applicability in diverse areas including biomedical engineering and the healthcare sector. It covers important topics such as FET biosensors, optical biosensors and advanced optical materials. It further showcases the significance of smart technologies such as artificial intelligence, machine learning and the internet of things for the biomedical and healthcare industries. It will serve as an ideal design book for senior undergraduate, graduate students, and academic researchers in the fields including electrical engineering, electronics and communication engineering, computer engineering and biomedical engineering.

Analog Integrated Circuit Design Automation

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Author :
Publisher : Springer
ISBN 13 : 3319340603
Total Pages : 207 pages
Book Rating : 4.09/5 ( download)

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Book Synopsis Analog Integrated Circuit Design Automation by : Ricardo Martins

Download or read book Analog Integrated Circuit Design Automation written by Ricardo Martins and published by Springer. This book was released on 2016-07-20 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces readers to a variety of tools for analog layout design automation. After discussing the placement and routing problem in electronic design automation (EDA), the authors overview a variety of automatic layout generation tools, as well as the most recent advances in analog layout-aware circuit sizing. The discussion includes different methods for automatic placement (a template-based Placer and an optimization-based Placer), a fully-automatic Router and an empirical-based Parasitic Extractor. The concepts and algorithms of all the modules are thoroughly described, enabling readers to reproduce the methodologies, improve the quality of their designs, or use them as starting point for a new tool. All the methods described are applied to practical examples for a 130nm design process, as well as placement and routing benchmark sets.