Machine Learning Applications In Electronic Design Automation

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Machine Learning Applications in Electronic Design Automation

Author : Haoxing Ren
Publisher : Springer Nature
ISBN 13 : 303113074X
Total Pages : 585 pages
Book Rating : 4.0/5 (311 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

Author : Rohit Sharma
Publisher :
ISBN 13 : 9781980554356
Total Pages : 219 pages
Book Rating : 4.5/5 (543 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

Author : Ibrahim (Abe) M. Elfadel
Publisher : Springer
ISBN 13 : 3030046664
Total Pages : 694 pages
Book Rating : 4.0/5 (3 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

2021 11th International Conference on Advanced Computer Information Technologies (ACIT)

Author : IEEE Staff
Publisher :
ISBN 13 : 9781665448208
Total Pages : pages
Book Rating : 4.4/5 (482 download)

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Book Synopsis 2021 11th International Conference on Advanced Computer Information Technologies (ACIT) by : IEEE Staff

Download or read book 2021 11th International Conference on Advanced Computer Information Technologies (ACIT) written by IEEE Staff and published by . This book was released on 2021-09-15 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: providing podium for scientists to present the results of their research and scientific results in the field of advanced computer information technologies motivation for scientific activity exchange of advanced ideas and research results development of creativity in scientific activity

Using Artificial Neural Networks for Analog Integrated Circuit Design Automation

Author : João P. S. Rosa
Publisher : Springer Nature
ISBN 13 : 3030357430
Total Pages : 117 pages
Book Rating : 4.0/5 (33 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.

Machine Learning Techniques for VLSI Chip Design

Author : Abhishek Kumar
Publisher : John Wiley & Sons
ISBN 13 : 1119910471
Total Pages : 244 pages
Book Rating : 4.1/5 (199 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.

Automated Machine Learning

Author : Frank Hutter
Publisher : Springer
ISBN 13 : 3030053180
Total Pages : 223 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Automated Machine Learning by : Frank Hutter

Download or read book Automated Machine Learning written by Frank Hutter and published by Springer. This book was released on 2019-05-17 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of AutoML systems. The recent success of commercial ML applications and the rapid growth of the field has created a high demand for off-the-shelf ML methods that can be used easily and without expert knowledge. However, many of the recent machine learning successes crucially rely on human experts, who manually select appropriate ML architectures (deep learning architectures or more traditional ML workflows) and their hyperparameters. To overcome this problem, the field of AutoML targets a progressive automation of machine learning, based on principles from optimization and machine learning itself. This book serves as a point of entry into this quickly-developing field for researchers and advanced students alike, as well as providing a reference for practitioners aiming to use AutoML in their work.

Modern Approaches in Machine Learning and Cognitive Science: A Walkthrough

Author : Vinit Kumar Gunjan
Publisher : Springer Nature
ISBN 13 : 3031430093
Total Pages : 337 pages
Book Rating : 4.0/5 (314 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

Author : Ankur Kumar
Publisher : CRC Press
ISBN 13 : 1000932346
Total Pages : 218 pages
Book Rating : 4.0/5 (9 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.

Frontiers of Quality Electronic Design (QED)

Author : Ali Iranmanesh
Publisher : Springer Nature
ISBN 13 : 3031163443
Total Pages : 690 pages
Book Rating : 4.0/5 (311 download)

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Book Synopsis Frontiers of Quality Electronic Design (QED) by : Ali Iranmanesh

Download or read book Frontiers of Quality Electronic Design (QED) written by Ali Iranmanesh and published by Springer Nature. This book was released on 2023-01-11 with total page 690 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quality Electronic Design (QED)’s landscape spans a vast region where territories of many participating disciplines and technologies overlap. This book explores the latest trends in several key topics related to quality electronic design, with emphasis on Hardware Security, Cybersecurity, Machine Learning, and application of Artificial Intelligence (AI). The book includes topics in nonvolatile memories (NVM), Internet of Things (IoT), FPGA, and Neural Networks.

Automated Machine Learning in Action

Author : Qingquan Song
Publisher : Simon and Schuster
ISBN 13 : 1617298050
Total Pages : 334 pages
Book Rating : 4.6/5 (172 download)

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Book Synopsis Automated Machine Learning in Action by : Qingquan Song

Download or read book Automated Machine Learning in Action written by Qingquan Song and published by Simon and Schuster. This book was released on 2022-06-07 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: Automated Machine Learning in Action reveals how you can automate the burdensome elements of designing and tuning your machine learning systems. --

Nanoelectronics and Photonics

Author : Anatoli Korkin
Publisher : Springer Science & Business Media
ISBN 13 : 0387764992
Total Pages : 484 pages
Book Rating : 4.3/5 (877 download)

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Book Synopsis Nanoelectronics and Photonics by : Anatoli Korkin

Download or read book Nanoelectronics and Photonics written by Anatoli Korkin and published by Springer Science & Business Media. This book was released on 2008-09-23 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nanoelectronics and Photonics provides a fundamental description of the core elements and problems of advanced and future information technology. The authoritative book collects a series of tutorial chapters from leaders in the field covering fundamental topics from materials to devices and system architecture, and bridges the fundamental laws of physics and chemistry of materials at the atomic scale with device and circuit design and performance requirements.

Analog Integrated Circuit Design Automation

Author : Ricardo Martins
Publisher : Springer
ISBN 13 : 3319340603
Total Pages : 207 pages
Book Rating : 4.3/5 (193 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.

Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing

Author : Sudeep Pasricha
Publisher : Springer Nature
ISBN 13 : 3031399323
Total Pages : 481 pages
Book Rating : 4.0/5 (313 download)

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Book Synopsis Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing by : Sudeep Pasricha

Download or read book Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing written by Sudeep Pasricha and published by Springer Nature. This book was released on 2023-10-09 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent advances towards the goal of enabling efficient implementation of machine learning models on resource-constrained systems, covering different application domains. The focus is on presenting interesting and new use cases of applying machine learning to innovative application domains, exploring the efficient hardware design of efficient machine learning accelerators, memory optimization techniques, illustrating model compression and neural architecture search techniques for energy-efficient and fast execution on resource-constrained hardware platforms, and understanding hardware-software codesign techniques for achieving even greater energy, reliability, and performance benefits. Discusses efficient implementation of machine learning in embedded, CPS, IoT, and edge computing; Offers comprehensive coverage of hardware design, software design, and hardware/software co-design and co-optimization; Describes real applications to demonstrate how embedded, CPS, IoT, and edge applications benefit from machine learning.

Artificial Intelligence in Healthcare

Author : Adam Bohr
Publisher : Academic Press
ISBN 13 : 0128184396
Total Pages : 385 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Artificial Intelligence in Healthcare by : Adam Bohr

Download or read book Artificial Intelligence in Healthcare written by Adam Bohr and published by Academic Press. This book was released on 2020-06-21 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. Highlights different data techniques in healthcare data analysis, including machine learning and data mining Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks Includes applications and case studies across all areas of AI in healthcare data

Natural Language Processing for Electronic Design Automation

Author : Mathias Soeken
Publisher : Springer Nature
ISBN 13 : 3030522733
Total Pages : 115 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis Natural Language Processing for Electronic Design Automation by : Mathias Soeken

Download or read book Natural Language Processing for Electronic Design Automation written by Mathias Soeken and published by Springer Nature. This book was released on 2020-08-31 with total page 115 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes approaches for integrating more automation to the early stages of EDA design flows. Readers will learn how natural language processing techniques can be utilized during early design stages, in order to automate the requirements engineering process and the translation of natural language specifications into formal descriptions. This book brings together leading experts to explain the state-of-the-art in natural language processing, enabling designers to integrate these techniques into algorithms, through existing frameworks.

Machine Learning for Healthcare Applications

Author : Sachi Nandan Mohanty
Publisher : John Wiley & Sons
ISBN 13 : 1119791812
Total Pages : 418 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Machine Learning for Healthcare Applications by : Sachi Nandan Mohanty

Download or read book Machine Learning for Healthcare Applications written by Sachi Nandan Mohanty and published by John Wiley & Sons. This book was released on 2021-04-13 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: When considering the idea of using machine learning in healthcare, it is a Herculean task to present the entire gamut of information in the field of intelligent systems. It is, therefore the objective of this book to keep the presentation narrow and intensive. This approach is distinct from others in that it presents detailed computer simulations for all models presented with explanations of the program code. It includes unique and distinctive chapters on disease diagnosis, telemedicine, medical imaging, smart health monitoring, social media healthcare, and machine learning for COVID-19. These chapters help develop a clear understanding of the working of an algorithm while strengthening logical thinking. In this environment, answering a single question may require accessing several data sources and calling on sophisticated analysis tools. While data integration is a dynamic research area in the database community, the specific needs of research have led to the development of numerous middleware systems that provide seamless data access in a result-driven environment. Since this book is intended to be useful to a wide audience, students, researchers and scientists from both academia and industry may all benefit from this material. It contains a comprehensive description of issues for healthcare data management and an overview of existing systems, making it appropriate for introductory and instructional purposes. Prerequisites are minimal; the readers are expected to have basic knowledge of machine learning. This book is divided into 22 real-time innovative chapters which provide a variety of application examples in different domains. These chapters illustrate why traditional approaches often fail to meet customers’ needs. The presented approaches provide a comprehensive overview of current technology. Each of these chapters, which are written by the main inventors of the presented systems, specifies requirements and provides a description of both the chosen approach and its implementation. Because of the self-contained nature of these chapters, they may be read in any order. Each of the chapters use various technical terms which involve expertise in machine learning and computer science.