Vlsi For Artificial Intelligence
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Vlsi For Artificial Intelligence
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Author : Jose G. Delgado-Frias
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Vlsi For Artificial Intelligence written by Jose G. Delgado-Frias and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Technology & Engineering categories.
Vlsi For Artificial Intelligence And Neural Networks
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Author : Jose G. Delgado-Frias
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Vlsi For Artificial Intelligence And Neural Networks written by Jose G. Delgado-Frias and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
This book is an edited selection of the papers presented at the International Workshop on VLSI for Artifidal Intelligence and Neural Networks which was held at the University of Oxford in September 1990. Our thanks go to all the contributors and especially to the programme committee for all their hard work. Thanks are also due to the ACM-SIGARCH, the IEEE Computer Society, and the lEE for publicizing the event and to the University of Oxford and SUNY-Binghamton for their active support. We are particularly grateful to Anna Morris, Maureen Doherty and Laura Duffy for coping with the administrative problems. Jose Delgado-Frias Will Moore April 1991 vii PROLOGUE Artificial intelligence and neural network algorithms/computing have increased in complexity as well as in the number of applications. This in tum has posed a tremendous need for a larger computational power than can be provided by conventional scalar processors which are oriented towards numeric and data manipulations. Due to the artificial intelligence requirements (symbolic manipulation, knowledge representation, non-deterministic computations and dynamic resource allocation) and neural network computing approach (non-programming and learning), a different set of constraints and demands are imposed on the computer architectures for these applications.
Vlsi For Neural Networks And Artificial Intelligence
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Author : Jose G. Delgado-Frias
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-06-29
Vlsi For Neural Networks And Artificial Intelligence written by Jose G. Delgado-Frias and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-29 with Computers categories.
Neural network and artificial intelligence algorithrns and computing have increased not only in complexity but also in the number of applications. This in turn has posed a tremendous need for a larger computational power that conventional scalar processors may not be able to deliver efficiently. These processors are oriented towards numeric and data manipulations. Due to the neurocomputing requirements (such as non-programming and learning) and the artificial intelligence requirements (such as symbolic manipulation and knowledge representation) a different set of constraints and demands are imposed on the computer architectures/organizations for these applications. Research and development of new computer architectures and VLSI circuits for neural networks and artificial intelligence have been increased in order to meet the new performance requirements. This book presents novel approaches and trends on VLSI implementations of machines for these applications. Papers have been drawn from a number of research communities; the subjects span analog and digital VLSI design, computer design, computer architectures, neurocomputing and artificial intelligence techniques. This book has been organized into four subject areas that cover the two major categories of this book; the areas are: analog circuits for neural networks, digital implementations of neural networks, neural networks on multiprocessor systems and applications, and VLSI machines for artificial intelligence. The topics that are covered in each area are briefly introduced below.
An Artificial Intelligence Approach To Vlsi Design
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Author : Thaddeus J. Kowalski
language : en
Publisher: Springer International Series in Engineering and Computer Science
Release Date : 1985-05-31
An Artificial Intelligence Approach To Vlsi Design written by Thaddeus J. Kowalski and has been published by Springer International Series in Engineering and Computer Science this book supported file pdf, txt, epub, kindle and other format this book has been release on 1985-05-31 with Computers categories.
Vlsi And Hardware Implementations Using Modern Machine Learning Methods
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Author : Sandeep Saini
language : en
Publisher: CRC Press
Release Date : 2021-12-30
Vlsi And Hardware Implementations Using Modern Machine Learning Methods written by Sandeep Saini and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-30 with Technology & Engineering categories.
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.
Vlsi And Parallel Computing For Pattern Recognition And Artificial Intelligence
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Author : N Ranganathan
language : en
Publisher: World Scientific
Release Date : 1995-06-30
Vlsi And Parallel Computing For Pattern Recognition And Artificial Intelligence written by N Ranganathan and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995-06-30 with Computers categories.
This book covers parallel algorithms and architectures and VLSI chips for a range of problems in image processing, computer vision, pattern recognition and artificial intelligence. The specific problems addressed include vision and image processing tasks, Fast Fourier Transforms, Hough Transforms, Discrete Cosine Transforms, image compression, polygon matching, template matching, pattern matching, fuzzy expert systems and image rotation. The collection of papers gives the reader a good introduction to the state-of-the-art, while for an expert this serves as a good reference and a source of some new contributions in this field.
Artificial Intelligence And Automation
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Author : Nikolas G Bourbakis
language : en
Publisher: World Scientific
Release Date : 1998-05-05
Artificial Intelligence And Automation written by Nikolas G Bourbakis and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-05-05 with Computers categories.
Contents:A New Way to Acquire Knowledge (H-Y Wang)An SPN Knowledge Representation Scheme (J Gattiker & N Bourbakis)On the Deep Structures of Word Problems and Their Construction (F Gomez)Resolving Conflicts in Inheritance Reasoning with Statistical Approach (C W Lee)Integrating High and Low Level Computer Vision for Scene Understanding (R Malik & S So)The Evolution of Commercial AI Tools: The First Decade (F Hayes-Roth)Reengineering: The AI Generation — Billions on the Table (J S Minor Jr)An Intelligent Tool for Discovering Data Dependencies in Relational DBS (P Gavaskar & F Golshani)A Case-Based Reasoning (CBR) Tool to Assist Traffic Flow (B Das & S Bayles)A Study of Financial Expert System Based on Flops (T Kaneko & K Takenaka)An Associative Data Parallel Compilation Model for Tight Integration of High Performance Knowledge Retrieval and Computation (A K Bansal)Software Automation: From Silly to Intelligent (J-F Xu et al.)Software Engineering Using Artificial Intelligence: The Knowledge Based Software Assistant (D White)Knowledge Based Derivation of Programs from Specifications (T Weight et al.)Automatic Functional Model Generation for Parallel Fault Design Error Simulations (S-E Chang & S A Szygenda)Visual Reverse Engineering Using SPNs for Automated Diagnosis and Functional Simulation of Digital Circuits (J Gattiker & S Mertoguno)The Impact of AI in VLSI Design Automation (M Mortazavi & N Bourbakis)The Automated Acquisition of Subcategorizations of Verbs, Nouns and Adjectives from Sample Sentences (F Gomez)General Method for Planning and Rendezvous Problems (K I Trovato)Learning to Improve Path Planning Performance (P C Chen)Incremental Adaptation as a Method to Improve Reactive Behavior (A J Hendriks & D M Lyons)An SPN-Neural Planning Methodology for Coordination of Multiple Robotic Arms with Constrained Placement (N Bourbakis & A Tascillo) Readership: Computer scientists, artificial intelligence practitioners and robotics users. keywords:
An Artificial Intelligence Approach To Vlsi Routing
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Author : R. Joobbani
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
An Artificial Intelligence Approach To Vlsi Routing written by R. Joobbani and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Technology & Engineering categories.
Routing of VLSI chips is an important, time consuming, and difficult problem. The difficulty of the problem is attributed to the large number of often conflicting factors that affect the routing quality. Traditional techniques have approached routing by ignoring some of these factors and imposing unnecessary constraints in order to make routing tractable. In addition to the imposition of these restrictions, which simplify the problems to a degree but at the same time reduce the routing quality, traditional approaches use brute force. They often transform the problem into mathematical or graph problems and completely ignore the specific knowledge about the routing task that can greatly help the solution. This thesis overcomes some of the above problems and presents a system that performs routing close to what human designers do. In other words it heavily capitalizes on the knowledge of human expertise in this area, it does not impose unnecessary constraints, it considers all the different factors that affect the routing quality, and most importantly it allows constant user interaction throughout the routing process. To achieve the above, this thesis presents background about some representative techniques for routing and summarizes their characteristics. It then studies in detail the different factors (such as minimum area, number of vias, wire length, etc.) that affect the routing quality, and the different criteria (such as vertical/horizontal constraint graph, merging, minimal rectilinear Steiner tree, etc.) that can be used to optimize these factors.
Machine Learning In Vlsi Computer Aided Design
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Author : Ibrahim (Abe) M. Elfadel
language : en
Publisher: Springer
Release Date : 2019-03-15
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 2019-03-15 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
Integrated Devices For Artificial Intelligence And Vlsi
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Author : Balwinder Raj
language : en
Publisher: Wiley-Scrivener
Release Date : 2024-09-04
Integrated Devices For Artificial Intelligence And Vlsi written by Balwinder Raj and has been published by Wiley-Scrivener this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-04 with Technology & Engineering categories.
Very large-scale integration (VLSI) is the inter-disciplinary science of utilizing advanced semiconductor technology to create various functions of computer system. This book addresses the close link of microelectronics and artificial intelligence (AI). By combining VLSI technology, a very powerful computer architecture confinement is possible. To overcome problems at different design stages, researchers introduced artificial intelligent (AI) techniques in VLSI design automation. AI techniques, such as knowledge-based and expert systems, first try to define the problem and then choose the best solution from the domain of possible solutions. These days, several CAD technologies, such as Synopsys and Mentor Graphics, are specifically created to increase the automation of VLSI design. When a task is completed using the appropriate tool, each stage of the task design produces outcomes that are more productive than typical. However, combining all of these tools into a single package offer has drawbacks. We can't really use every outlook without sacrificing the efficiency and usefulness of our output. The researchers decided to include AI approaches into VLSI design automation in order to get around these obstacles. AI is one of the fastest growing tools in the world of technology and innovation that helps to make computers more reliable and easy to use. Artificial Intelligence in VLSI design has provided high-end and more feasible solutions to the difficulties faced by the VLSI industry. Physical design, RTL design, STA, etc. are some of the most in-demand courses to enter the VLSI industry. These courses help develop a better understanding of the many tools like Synopsis. With each new dawn, artificial intelligence in VLSI design is continually evolving, and new opportunities are being investigated.