Machine Learning Applications In Electronic Design Automation
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Machine Learning Applications In Electronic Design Automation
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Author : Haoxing Ren
language : en
Publisher: Springer Nature
Release Date : 2023-01-01
Machine Learning Applications In Electronic Design Automation written by Haoxing Ren and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-01 with Technology & Engineering categories.
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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Author : Rohit Sharma
language : en
Publisher:
Release Date : 2018-03-13
Machine Intelligence In Design Automation written by Rohit Sharma and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-13 with categories.
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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Author : Ibrahim (Abe) M. Elfadel
language : en
Publisher: Springer
Release Date : 2019-03-16
Machine Learning In Vlsi Computer Aided Design written by Ibrahim (Abe) M. Elfadel and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-16 with Technology & Engineering categories.
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
Ai Enabled Electronic Circuit And System Design
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Author : Ali Iranmanesh
language : en
Publisher: Springer Nature
Release Date : 2025-01-27
Ai Enabled Electronic Circuit And System Design written by Ali Iranmanesh and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-27 with Computers categories.
As our world becomes increasingly digital, electronics underpin nearly every industry. Understanding how AI enhances this foundational technology can unlock innovations, from smarter homes to more powerful gadgets, offering vast opportunities for businesses and consumers alike. This book demystifies how AI streamlines the creation of electronic systems, making them smarter and more efficient. With AI’s transformative impact on various engineering fields, this resource provides an up-to-date exploration of these advancements, authored by experts actively engaged in this dynamic field. Stay ahead in the rapidly evolving landscape of AI in engineering with “AI-Enabled Electronic Circuit and System Design: From Ideation to Utilization,” your essential guide to the future of electronic systems. !--[endif]--A transformative guide describing how revolutionizes electronic design through AI integration. Highlighting trends, challenges and opportunities; Demystifies complex AI applications in electronic design for practical use; Leading insights, authored by top experts actively engaged in the field; Offers a current, relevant exploration of significant topics in AI’s role in electronic circuit and system design. Editor’s bios. Dr. Ali A. Iranmanesh is the founder and CEO of Silicon Valley Polytechnic Institute. He has received his Bachelor of Science in Electrical Engineering from Sharif University of Technology (SUT), Tehran, Iran, and both his master’s and Ph.D. degrees in Electrical Engineering and Physics from Stanford University in Stanford, CA. He additionally holds a master’s degree in business administration (MBA) from San Jose State University in San Jose, CA. Dr. Iranmanesh is the founder and chairman of the International Society for Quality Electronic Design (ISQED). Currently, he serves as the CEO of Innovotek. Dr. Iranmanesh has been instrumental in advancing semiconductor technologies, innovative design methodologies, and engineering education. He holds nearly 100 US and international patents, reflecting his signifi cant contributions to the field. Dr. Iranmanesh is the Senior life members of EEE, senior member of the American Society for Quality, co-founder and Chair Emeritus of the IEEE Education Society of Silicon Valley, Vice Chair Emeritus of the IEEE PV chapter, and recipient of IEEE Outstanding Educator Award. Dr. Hossein Sayadi is a Tenure-Track Assistant Professor and Associate Chair in the Department of Computer Engineering and Computer Science at California State University, Long Beach (CSULB). He earned his Ph.D. in Electrical and Computer Engineering from George Mason University in Fairfax, Virginia, and an M.Sc. in Computer Engineering from Sharif University of Technology in Tehran, Iran. As a recognized researcher with over 14 years of research experience, Dr. Sayadi is the founder and director of the Intelligent, Secure, and Energy-Efficient Computing (iSEC) Lab at CSULB. His research focuses on advancing hardware security and trust, AI and machine learning, cybersecurity, and energy-efficient computing, addressing critical challenges in modern computing and cyber-physical systems. He has authored over 75 peer-reviewed publications in leading conferences and journals. Dr. Sayadi is the CSU STEM-NET Faculty Fellow, with his research supported by multiple National Science Foundation (NSF) grants and awards from CSULB and the CSU Chancellor’s Office. He has contributed to various international conferences as an organizer and program committee member, including as the TPC Chair for the 2024 and 2025 IEEE ISQED.
Using Artificial Neural Networks For Analog Integrated Circuit Design Automation
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Author : João P. S. Rosa
language : en
Publisher: Springer Nature
Release Date : 2019-12-11
Using Artificial Neural Networks For Analog Integrated Circuit Design Automation written by João P. S. Rosa and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-11 with Technology & Engineering categories.
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.
Analog Integrated Circuit Design Automation
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Author : Ricardo Martins
language : en
Publisher: Springer
Release Date : 2016-07-20
Analog Integrated Circuit Design Automation written by Ricardo Martins and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-20 with Technology & Engineering categories.
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.
Proceedings Of The Third International Conference On Cognitive And Intelligent Computing Volume 2
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Author : Amit Kumar
language : en
Publisher: Springer Nature
Release Date : 2025-02-25
Proceedings Of The Third International Conference On Cognitive And Intelligent Computing Volume 2 written by Amit Kumar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-25 with Computers categories.
This book presents original, peer-reviewed select articles from the International Conference on Cognitive and Intelligent Computing (ICCIC-2023), held on December 8–9, 2023, at Hyderabad, in India. The book focuses on the comprehensive nature of computational intelligence, cognitive computing, AI, ML, and DL in order to highlight its role in the modelling, identification, optimisation, prediction, forecasting, and control of future intelligent systems. It includes contributions from a methodological/application standpoint in understanding artificial intelligence and machine learning approaches and their capabilities in solving a wide range of problems in the real world.
Modern Approaches In Machine Learning And Cognitive Science A Walkthrough
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Author : Vinit Kumar Gunjan
language : en
Publisher: Springer Nature
Release Date : 2024-01-13
Modern Approaches In Machine Learning And Cognitive Science A Walkthrough written by Vinit Kumar Gunjan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-13 with Computers categories.
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.
Automated Database Applications Testing
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Author : Rana Farid Mikhail
language : en
Publisher: World Scientific
Release Date : 2010
Automated Database Applications Testing written by Rana Farid Mikhail and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Computers categories.
This book introduces SpecDB, an intelligent database created to represent and host software specifications in a machine-readable format, based on the principles of artificial intelligence and unit testing database operations. SpecDB is demonstrated via two automated intelligent tools. The first automatically generates database constraints from a rule-base in SpecDB. The second is a reverse engineering tool that logs the actual execution of the program from the code.
Machine Learning For Robotics Applications
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Author : Monica Bianchini
language : en
Publisher: Springer Nature
Release Date : 2021-04-23
Machine Learning For Robotics Applications written by Monica Bianchini and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-23 with Technology & Engineering categories.
Machine learning has become one of the most prevalent topics in recent years. The application of machine learning we see today is a tip of the iceberg. The machine learning revolution has just started to roll out. It is becoming an integral part of all modern electronic devices. Applications in automation areas like automotive, security and surveillance, augmented reality, smart home, retail automation and healthcare are few of them. Robotics is also rising to dominate the automated world. The future applications of machine learning in the robotics area are still undiscovered to the common readers. We are, therefore, putting an effort to write this edited book on the future applications of machine learning on robotics where several applications have been included in separate chapters. The content of the book is technical. It has been tried to cover all possible application areas of Robotics using machine learning. This book will provide the future vision on the unexplored areas of applications of Robotics using machine learning. The ideas to be presented in this book are backed up by original research results. The chapter provided here in-depth look with all necessary theory and mathematical calculations. It will be perfect for laymen and developers as it will combine both advanced and introductory material to form an argument for what machine learning could achieve in the future. It will provide a vision on future areas of application and their approach in detail. Therefore, this book will be immensely beneficial for the academicians, researchers and industry project managers to develop their new project and thereby beneficial for mankind. Original research and review works with model and build Robotics applications using Machine learning are included as chapters in this book.