Download or read book Parallel Algorithms for Machine Intelligence and Vision written by Vipin Kumar and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 445 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent research results in the area of parallel algorithms for problem solving, search, natural language parsing, and computer vision, are brought together in this book. The research reported demonstrates that substantial parallelism can be exploited in various machine intelligence and vision problems. The chapter authors are prominent researchers actively involved in the study of parallel algorithms for machine intelligence and vision. Extensive experimental studies are presented that will help the reader in assessing the usefulness of an approach to a specific problem. Intended for students and researchers actively involved in parallel algorithms design and in machine intelligence and vision, this book will serve as a valuable reference work as well as an introduction to several research directions in these areas.
Download or read book Parallel Processing for Artificial Intelligence 1 written by L.N. Kanal and published by Elsevier. This book was released on 2014-06-28 with total page 445 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Parallel Architectures and Parallel Algorithms for Integrated Vision Systems written by Alok N Choudary and published by . This book was released on 1990-09-30 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer vision has been regarded as one of the most complex and computationally intensive problems. An integrated vision system (IVS) is a system that uses vision algorithms from all levels of processing to perform for a high level application (e.g, object recognition). This thesis addresses several issues in parallel architectures and parallel algorithms for integrated vision systems. First, a model of computation for IVSs is presented. The model captures computational requirements, defines spatial and temporal data dependencies between tasks, and shows what types of interactions may occur between tasks from different levels of processing. The model is used to develop features and capabilities of a parallel architecture suitable for IVSs. A multiprocessor architecture for IVSs (called NETRA) is presented. NETRA is highly flexible without the use of complex interconnection schemes. NETRA is recursively defined hierarchical architecture whose leaf nodes consist of clusters processors connected with a programmable crossbar with a selective broadcast capability. Hence, it is easily scalable from small to large systems. Homogeneity of NETRA permits fault tolerance and graceful degradation under faults. Several refinements in the architecture over the original design are also proposed. Performance of several vision algorithms when they are mapped on one cluster is presented. It is shown that SIMD, MIMD and systolic algorithms can be easily mapped onto processor clusters, and almost linear speedups are possible. An extensive analysis of inter-cluster communication strategies in NETRA is presented. A methodology to evaluate performance of algorithms on NETRA is described. Performance analysis of parallel algorithms when mapped across clusters is presented. The parameters are derived from the characteristics of the parallel algorithms, which are then, used to evaluate the alternative communication strategies in NETRA. The effects of communication interference on the performance of algorithms are studied. It is observed that if communication speeds are matched with the computation speeds, almost linear speedups are possible when algorithms are mapped across clusters. Finally, several techniques to perform data decomposition, and static and dynamic load balancing for IVS algorithms are described. These techniques can be used to perform load balancing for intermediate and high level, data dependent vision algorithms. They are shown to perform well, using them on an implementation of a motion estimation system on a hypercube multiprocessor. (Abstract shortened with permission of author.)
Download or read book Parallel Processing for Artificial Intelligence 3 written by J. Geller and published by Elsevier. This book was released on 1997-02-10 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Parallel Algorithms for Computer Vision on the Connection Machine written by Massachusetts Institute of Technology. Artificial Intelligence Laboratory and published by . This book was released on 1986 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Vlsi And Parallel Computing For Pattern Recognition And Artificial Intelligence written by N Ranganathan and published by World Scientific. This book was released on 1995-06-30 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Parallel Algorithms for Computer Vision on the Connection Machine written by James Joseph Little and published by . This book was released on 1986 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Connection Machine is a fine-grained parallel computer having up to 64K processors. It supports both local communication among the processors, which are situated in a two-dimensional mesh, and high bandwidth communication among processors at arbitrary locations, using a message-passing network. We present solutions to a set of Image Understanding problems for the Connection Machine. These problems were proposed by DARPA to evaluate architectures for Image Understanding systems, and are intended to comprise a representative sample of fundamental procedures to be used in Image Understanding. The solutions on the Connection Machine embody general methods for filtering images, determining connectivity among image elements, determining spatial relations of image elements and computing graph properties, such as matchings and shortest paths.
Download or read book Parallel Algorithms in Computational Science and Engineering written by Ananth Grama and published by Springer Nature. This book was released on 2020-07-06 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: This contributed volume highlights two areas of fundamental interest in high-performance computing: core algorithms for important kernels and computationally demanding applications. The first few chapters explore algorithms, numerical techniques, and their parallel formulations for a variety of kernels that arise in applications. The rest of the volume focuses on state-of-the-art applications from diverse domains. By structuring the volume around these two areas, it presents a comprehensive view of the application landscape for high-performance computing, while also enabling readers to develop new applications using the kernels. Readers will learn how to choose the most suitable parallel algorithms for any given application, ensuring that theory and practicality are clearly connected. Applications using these techniques are illustrated in detail, including: Computational materials science and engineering Computational cardiovascular analysis Multiscale analysis of wind turbines and turbomachinery Weather forecasting Machine learning techniques Parallel Algorithms in Computational Science and Engineering will be an ideal reference for applied mathematicians, engineers, computer scientists, and other researchers who utilize high-performance computing in their work.
Download or read book Recent Advances in Computer Vision Applications Using Parallel Processing written by Khalid M. Hosny and published by Springer Nature. This book was released on 2023-01-23 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive book is primarily intended for researchers, computer vision specialists, and high-performance computing specialists who are interested in parallelizing computer vision techniques for the sake of accelerating the run-time of computer vision methods. This book covers different penalization methods on different parallel architectures such as multi-core CPUs and GPUs. It is also a valuable reference resource for researchers at all levels (e.g., undergraduate and postgraduate) who are seeking real-life examples of speeding up the computer vision methods’ run-time.
Download or read book Parallel Processing for Artificial Intelligence 2 written by V. Kumar and published by Elsevier. This book was released on 2014-06-28 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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!
Download or read book Parallel Computation and Computers for Artificial Intelligence written by J.S. Kowalik and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 305 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Parallel Image Processing written by M Nivat and published by World Scientific. This book was released on 1992-10-29 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contents:Three-Dimensional Object Pattern Representation by Array Grammars (P S P Wang)Stochastic Puzzle Grammars (R Siromoney et al.)Parallel Recognition of High Dimensional Images (M Nivat & A Saoudi)Two-Dimensional Uniquely Parsable Isometric Array Grammars (Y Yamamoto & K Morita)Replicated Image Algorithms and Their Analyses on SIMD Machines (P J Narayanan & L S Davis)The Depth and Motion Analysis Machine (O D Faugeras et al.)Image Analysis on Massively Parallel Computers: An Architecture Point of View (A Mérigot & B Zavidovique)Parallel Algorithm for Colour Texture Generation Using the Random Neural Network Model (V Atalay & E Gelenbe)and other papers Readership: Computer scientists. keywords:
Download or read book Minimax and Applications written by Ding-Zhu Du and published by Springer Science & Business Media. This book was released on 2013-12-01 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Techniques and principles of minimax theory play a key role in many areas of research, including game theory, optimization, and computational complexity. In general, a minimax problem can be formulated as min max f(x, y) (1) ",EX !lEY where f(x, y) is a function defined on the product of X and Y spaces. There are two basic issues regarding minimax problems: The first issue concerns the establishment of sufficient and necessary conditions for equality minmaxf(x,y) = maxminf(x,y). (2) "'EX !lEY !lEY "'EX The classical minimax theorem of von Neumann is a result of this type. Duality theory in linear and convex quadratic programming interprets minimax theory in a different way. The second issue concerns the establishment of sufficient and necessary conditions for values of the variables x and y that achieve the global minimax function value f(x*, y*) = minmaxf(x, y). (3) "'EX !lEY There are two developments in minimax theory that we would like to mention.
Download or read book Parallel Processing and Parallel Algorithms written by Seyed H Roosta and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 579 pages. Available in PDF, EPUB and Kindle. Book excerpt: Motivation It is now possible to build powerful single-processor and multiprocessor systems and use them efficiently for data processing, which has seen an explosive ex pansion in many areas of computer science and engineering. One approach to meeting the performance requirements of the applications has been to utilize the most powerful single-processor system that is available. When such a system does not provide the performance requirements, pipelined and parallel process ing structures can be employed. The concept of parallel processing is a depar ture from sequential processing. In sequential computation one processor is in volved and performs one operation at a time. On the other hand, in parallel computation several processors cooperate to solve a problem, which reduces computing time because several operations can be carried out simultaneously. Using several processors that work together on a given computation illustrates a new paradigm in computer problem solving which is completely different from sequential processing. From the practical point of view, this provides sufficient justification to investigate the concept of parallel processing and related issues, such as parallel algorithms. Parallel processing involves utilizing several factors, such as parallel architectures, parallel algorithms, parallel programming lan guages and performance analysis, which are strongly interrelated. In general, four steps are involved in performing a computational problem in parallel. The first step is to understand the nature of computations in the specific application domain.
Download or read book Annual ACM Symposium on Parallel Algorithms and Architectures written by and published by . This book was released on 1994 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Parallel Architectures and Parallel Algorithms for Integrated Vision Systems written by Alok N. Choudary and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer vision is one of the most complex and computationally intensive problem. Like any other computationally intensive problems, parallel pro cessing has been suggested as an approach to solving the problems in com puter vision. Computer vision employs algorithms from a wide range of areas such as image and signal processing, advanced mathematics, graph theory, databases and artificial intelligence. Hence, not only are the comput ing requirements for solving vision problems tremendous but they also demand computers that are efficient to solve problems exhibiting vastly dif ferent characteristics. With recent advances in VLSI design technology, Single Instruction Multiple Data (SIMD) massively parallel computers have been proposed and built. However, such architectures have been shown to be useful for solving a very limited subset of the problems in vision. Specifically, algorithms from low level vision that involve computations closely mimicking the architec ture and require simple control and computations are suitable for massively parallel SIMD computers. An Integrated Vision System (IVS) involves com putations from low to high level vision to be executed in a systematic fashion and repeatedly. The interaction between computations and information dependent nature of the computations suggests that architectural require ments for computer vision systems can not be satisfied by massively parallel SIMD computers.
Download or read book Parallel Algorithms written by Ioannis Pitas and published by . This book was released on 1993 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt:
