Machine Learning Applications in Electronic Design Automation

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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

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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

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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)

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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

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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

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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.

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 : 4.0/5 (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.

Automated Machine Learning

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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.

Opto-VLSI Devices and Circuits for Biomedical and Healthcare Applications

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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.

Essential Electronic Design Automation (EDA)

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Publisher : Prentice Hall Professional
ISBN 13 : 9780131828292
Total Pages : 256 pages
Book Rating : 4.8/5 (282 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.

VLSI and Hardware Implementations using Modern Machine Learning Methods

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Publisher : CRC Press
ISBN 13 : 1000523845
Total Pages : 292 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis VLSI and Hardware Implementations using Modern Machine Learning Methods by : Sandeep Saini

Download or read book VLSI and Hardware Implementations using Modern Machine Learning Methods written by Sandeep Saini and published by CRC Press. This book was released on 2021-12-31 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine 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.

Frontiers of Quality Electronic Design (QED)

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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.

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

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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.

Natural Language Processing for Electronic Design Automation

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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.

Analog Integrated Circuit Design Automation

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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.

VLSI-SoC: Design Trends

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Publisher : Springer Nature
ISBN 13 : 3030816419
Total Pages : 372 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis VLSI-SoC: Design Trends by : Andrea Calimera

Download or read book VLSI-SoC: Design Trends written by Andrea Calimera and published by Springer Nature. This book was released on 2021-07-14 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains extended and revised versions of the best papers presented at the 28th IFIP WG 10.5/IEEE International Conference on Very Large Scale Integration, VLSI-SoC 2020, held in Salt Lake City, UT, USA, in October 2020.* The 16 full papers included in this volume were carefully reviewed and selected from the 38 papers (out of 74 submissions) presented at the conference. The papers discuss the latest academic and industrial results and developments as well as future trends in the field of System-on-Chip (SoC) design, considering the challenges of nano-scale, state-of-the-art and emerging manufacturing technologies. In particular they address cutting-edge research fields like low-power design of RF, analog and mixed-signal circuits, EDA tools for the synthesis and verification of heterogenous SoCs, accelerators for cryptography and deep learning and on-chip Interconnection system, reliability and testing, and integration of 3D-ICs. *The conference was held virtually.

VLSI and Hardware Implementations using Modern Machine Learning Methods

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Author :
Publisher : CRC Press
ISBN 13 : 1000523810
Total Pages : 329 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis VLSI and Hardware Implementations using Modern Machine Learning Methods by : Sandeep Saini

Download or read book VLSI and Hardware Implementations using Modern Machine Learning Methods written by Sandeep Saini and published by CRC Press. This book was released on 2021-12-30 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. Illustrate latest techniques for device size and feature optimization. Highlight latest case studies and reviews of the methods used for hardware implementation.