Parallel Processing And Artificial Intelligence
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Parallel Computation And Computers For Artificial Intelligence
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Author : J.S. Kowalik
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Parallel Computation And Computers For Artificial Intelligence written by J.S. Kowalik 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.
It has been widely recognized that artificial intelligence computations offer large potential for distributed and parallel processing. Unfortunately, not much is known about designing parallel AI algorithms and efficient, easy-to-use parallel computer architectures for AI applications. The field of parallel computation and computers for AI is in its infancy, but some significant ideas have appeared and initial practical experience has become available. The purpose of this book has been to collect in one volume contributions from several leading researchers and pioneers of AI that represent a sample of these ideas and experiences. This sample does not include all schools of thought nor contributions from all leading researchers, but it covers a relatively wide variety of views and topics and in this sense can be helpful in assessing the state ofthe art. We hope that the book will serve, at least, as a pointer to more specialized literature and that it will stimulate interest in the area of parallel AI processing. It has been a great pleasure and a privilege to cooperate with all contributors to this volume. They have my warmest thanks and gratitude. Mrs. Birgitta Knapp has assisted me in the editorial task and demonstrated a great deal of skill and patience. Janusz S. Kowalik vii INTRODUCTION Artificial intelligence (AI) computer programs can be very time-consuming.
Parallel Processing And Artificial Intelligence
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Author : Mike Reeve
language : en
Publisher:
Release Date :
Parallel Processing And Artificial Intelligence written by Mike Reeve and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Parallel Processing For Artificial Intelligence 1
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Author : L.N. Kanal
language : en
Publisher: Elsevier
Release Date : 2014-06-28
Parallel Processing For Artificial Intelligence 1 written by L.N. Kanal and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-28 with Computers categories.
Parallel processing for AI problems is of great current interest because of its potential for alleviating the computational demands of AI procedures. The articles in this book consider parallel processing for problems in several areas of artificial intelligence: image processing, knowledge representation in semantic networks, production rules, mechanization of logic, constraint satisfaction, parsing of natural language, data filtering and data mining. The publication is divided into six sections. The first addresses parallel computing for processing and understanding images. The second discusses parallel processing for semantic networks, which are widely used means for representing knowledge - methods which enable efficient and flexible processing of semantic networks are expected to have high utility for building large-scale knowledge-based systems. The third section explores the automatic parallel execution of production systems, which are used extensively in building rule-based expert systems - systems containing large numbers of rules are slow to execute and can significantly benefit from automatic parallel execution. The exploitation of parallelism for the mechanization of logic is dealt with in the fourth section. While sequential control aspects pose problems for the parallelization of production systems, logic has a purely declarative interpretation which does not demand a particular evaluation strategy. In this area, therefore, very large search spaces provide significant potential for parallelism. In particular, this is true for automated theorem proving. The fifth section considers the problem of constraint satisfaction, which is a useful abstraction of a number of important problems in AI and other fields of computer science. It also discusses the technique of consistent labeling as a preprocessing step in the constraint satisfaction problem. Section VI consists of two articles, each on a different, important topic. The first discusses parallel formulation for the Tree Adjoining Grammar (TAG), which is a powerful formalism for describing natural languages. The second examines the suitability of a parallel programming paradigm called Linda, for solving problems in artificial intelligence.Each of the areas discussed in the book holds many open problems, but it is believed that parallel processing will form a key ingredient in achieving at least partial solutions. It is hoped that the contributions, sourced from experts around the world, will inspire readers to take on these challenging areas of inquiry.
Parallel Processing For Artificial Intelligence 2
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Author : V. Kumar
language : en
Publisher: Elsevier
Release Date : 2014-06-28
Parallel Processing For Artificial Intelligence 2 written by V. Kumar and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-28 with Computers categories.
With the increasing availability of parallel machines and the raising of interest in large scale and real world applications, research on parallel processing for Artificial Intelligence (AI) is gaining greater importance in the computer science environment. Many applications have been implemented and delivered but the field is still considered to be in its infancy.This book assembles diverse aspects of research in the area, providing an overview of the current state of technology. It also aims to promote further growth across the discipline. Contributions have been grouped according to their subject: architectures (3 papers), languages (4 papers), general algorithms (6 papers), and applications (5 papers). The internationally sourced papers range from purely theoretical work, simulation studies, algorithm and architecture proposals, to implemented systems and their experimental evaluation.Since the book is a second volume in the parallel processing for AI series, it provides a continued documentation of the research and advances made in the field. The editors hope that it will inspire readers to investigate the possiblities for enhancing AI systems by parallel processing and to make new discoveries of their own!
Parallel Processing For Artificial Intelligence
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Author : Laveen N. Kanal
language : en
Publisher:
Release Date : 1994
Parallel Processing For Artificial Intelligence written by Laveen N. Kanal and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with Artificial intelligence categories.
Parallel Processing For Artificial Intelligence 3
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Author : J. Geller
language : en
Publisher: Elsevier
Release Date : 1997-02-10
Parallel Processing For Artificial Intelligence 3 written by J. Geller and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997-02-10 with Computers categories.
The third in an informal series of books about parallel processing for Artificial Intelligence, this volume is based on the assumption that the computational demands of many AI tasks can be better served by parallel architectures than by the currently popular workstations. However, no assumption is made about the kind of parallelism to be used. Transputers, Connection Machines, farms of workstations, Cellular Neural Networks, Crays, and other hardware paradigms of parallelism are used by the authors of this collection.The papers arise from the areas of parallel knowledge representation, neural modeling, parallel non-monotonic reasoning, search and partitioning, constraint satisfaction, theorem proving, parallel decision trees, parallel programming languages and low-level computer vision. The final paper is an experience report about applications of massive parallelism which can be said to capture the spirit of a whole period of computing history.This volume provides the reader with a snapshot of the state of the art in Parallel Processing for Artificial Intelligence.
Parallel And High Performance Computing In Artificial Intelligence
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Author : Mukesh Raghuwanshi
language : en
Publisher: CRC Press
Release Date : 2025-05-20
Parallel And High Performance Computing In Artificial Intelligence written by Mukesh Raghuwanshi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-20 with Computers categories.
Parallel and High-Performance Computing in Artificial Intelligence explores high-performance architectures for data-intensive applications as well as efficient analytical strategies to speed up data processing and applications in automation, machine learning, deep learning, healthcare, bioinformatics, natural language processing (NLP), and vision intelligence. The book’s two major themes are high-performance computing (HPC) architecture and techniques and their application in artificial intelligence. Highlights include: HPC use cases, application programming interfaces (APIs), and applications Parallelization techniques HPC for machine learning Implementation of parallel computing with AI in big data analytics HPC with AI in healthcare systems AI in industrial automation Coverage of HPC architecture and techniques includes multicore architectures, parallel-computing techniques, and APIs, as well as dependence analysis for parallel computing. The book also covers hardware acceleration techniques, including those for GPU acceleration to power big data systems. As AI is increasingly being integrated into HPC applications, the book explores emerging and practical applications in such domains as healthcare, agriculture, bioinformatics, and industrial automation. It illustrates technologies and methodologies to boost the velocity and scale of AI analysis for fast discovery. Data scientists and researchers can benefit from the book’s discussion on AI-based HPC applications that can process higher volumes of data, provide more realistic simulations, and guide more accurate predictions. The book also focuses on deep learning and edge computing methodologies with HPC and presents recent research on methodologies and applications of HPC in AI.
Parallel Processing For Artificial Intelligence
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Author : V. Kumar
language : en
Publisher:
Release Date : 1985
Parallel Processing For Artificial Intelligence written by V. Kumar and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1985 with Artificial intelligence categories.
Parallel Processing For Supercomputers And Artificial Intelligence
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Author : Kai Hwang
language : en
Publisher: McGraw-Hill Companies
Release Date : 1989
Parallel Processing For Supercomputers And Artificial Intelligence written by Kai Hwang and has been published by McGraw-Hill Companies this book supported file pdf, txt, epub, kindle and other format this book has been release on 1989 with Computers categories.
Parallel Processing For Artificial Intelligence
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Author : Laveen N. Kanal
language : en
Publisher:
Release Date : 1994
Parallel Processing For Artificial Intelligence written by Laveen N. Kanal and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with Artificial intelligence categories.
Parallel processing for AI problems is of great current interest because of its potential for alleviating the computational demands of AI procedures. The articles in this book consider parallel processing for problems in several areas of artificial intelligence: image processing, knowledge representation in semantic networks, production rules, mechanization of logic, constraint satisfaction, parsing of natural language, data filtering and data mining. The publication is divided into six sections. The first addresses parallel computing for processing and understanding images. The second discusses parallel processing for semantic networks, which are widely used means for representing knowledge - methods which enable efficient and flexible processing of semantic networks are expected to have high utility for building large-scale knowledge-based systems. The third section explores the automatic parallel execution of production systems, which are used extensively in building rule-based expert systems - systems containing large numbers of rules are slow to execute and can significantly benefit from automatic parallel execution. The exploitation of parallelism for the mechanization of logic is dealt with in the fourth section. While sequential control aspects pose problems for the parallelization of production systems, logic has a purely declarative interpretation which does not demand a particular evaluation strategy. In this area, therefore, very large search spaces provide significant potential for parallelism. In particular, this is true for automated theorem proving. The fifth section considers the problem of constraint satisfaction, which is a useful abstraction of a number of important problems in AI and other fields of computer science. It also discusses the technique of consistent labeling as a preprocessing step in the constraint satisfaction problem. Section VI consists of two articles, each on a different, important topic. The first discusses parallel formulation for the Tree Adjoining Grammar (TAG), which is a powerful formalism for describing natural languages. The second examines the suitability of a parallel programming paradigm called Linda, for solving problems in artificial intelligence. Each of the areas discussed in the book holds many open problems, but it is believed that parallel processing will form a key ingredient in achieving at least partial solutions. It is hoped that the contributions, sourced from experts around the world, will inspire readers to take on these challenging areas of inquiry.