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Multi Computer Architectures For Artificial Intelligence
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Book Synopsis Multi-Computer Architectures for Artificial Intelligence by : Leonard Uhr
Download or read book Multi-Computer Architectures for Artificial Intelligence written by Leonard Uhr and published by Wiley-Interscience. This book was released on 1987-02-20 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is the most current and complete evaluation of multi-computer networks. It presents an up-to-date and detailed survey which describes the large number of multi-computer architectures that have been built during the past few years, and the even greater variety that are presently being built, designed, and explored. Special emphasis is given to approaches that show promise for handling complex real-world problems in real time. Describes the range of problems that confront workers in artificial intelligence (AI), and explains some of the major approaches being taken by AI researchers, focusing on the robust, flexible, extremely fast (hence highly parallel) systems. Presents judgements and opinions as to the most promising multi-computer archtectures for AI--including a number of exciting multi-computer structures.
Book Synopsis Architectural Design of Multi-Agent Systems: Technologies and Techniques by : Lin, Hong
Download or read book Architectural Design of Multi-Agent Systems: Technologies and Techniques written by Lin, Hong and published by IGI Global. This book was released on 2007-05-31 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book is a compilation of advanced research results in architecture and modeling issues of multi-agent systems. It serves as a reference for research on system models, architectural design languages, methods and reasoning, module interface design, and design issues"--Provided by publisher.
Book Synopsis AI for Computer Architecture by : Lizhong Chen
Download or read book AI for Computer Architecture written by Lizhong Chen and published by Morgan & Claypool Publishers. This book was released on 2020-11-06 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews the application of machine learning in system-wide simulation and run-time optimization, and in many individual components such as caches/memories, branch predictors, networks-on-chip, and GPUs. Artificial intelligence has already enabled pivotal advances in diverse fields, yet its impact on computer architecture has only just begun. In particular, recent work has explored broader application to the design, optimization, and simulation of computer architecture. Notably, machine-learning-based strategies often surpass prior state-of-the-art analytical, heuristic, and human-expert approaches. The book further analyzes current practice to highlight useful design strategies and identify areas for future work, based on optimized implementation strategies, opportune extensions to existing work, and ambitious long term possibilities. Taken together, these strategies and techniques present a promising future for increasingly automated computer architecture designs.
Book Synopsis Objective Coordination in Multi-Agent System Engineering by : Michael Schumacher
Download or read book Objective Coordination in Multi-Agent System Engineering written by Michael Schumacher and published by Springer. This book was released on 2003-06-29 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt: Based on a suitably defined coordination model distinguishing between objective (inter-agent) coordination and subjective (intra-agent) coordination, this book addresses the engineering of multi-agent systems and thus contributes to closing the gap between research and applications in agent technology. After reviewing the state of the art, the author introduces the general coordination model ECM and the corresponding object-oriented coordination language STL++. The practicability of ECM/STL++ is illustrated by the simulation of a particular collective robotics application and the automation of an e-commerce trading system. Situated at the intersection of behavior-based artificial intelligence and concurrent and distributed systems, this monograph is of relevance to the agent R&D community approaching agent technology from the distributed artificial intelligence point of view as well as for the distributed systems community.
Book Synopsis Parallel Processing for Supercomputers and Artificial Intelligence by : Kai Hwang
Download or read book Parallel Processing for Supercomputers and Artificial Intelligence written by Kai Hwang and published by McGraw-Hill Companies. This book was released on 1989 with total page 712 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Learning Deep Architectures for AI by : Yoshua Bengio
Download or read book Learning Deep Architectures for AI written by Yoshua Bengio and published by Now Publishers Inc. This book was released on 2009 with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt: Theoretical results suggest that in order to learn the kind of complicated functions that can represent high-level abstractions (e.g. in vision, language, and other AI-level tasks), one may need deep architectures. Deep architectures are composed of multiple levels of non-linear operations, such as in neural nets with many hidden layers or in complicated propositional formulae re-using many sub-formulae. Searching the parameter space of deep architectures is a difficult task, but learning algorithms such as those for Deep Belief Networks have recently been proposed to tackle this problem with notable success, beating the state-of-the-art in certain areas. This paper discusses the motivations and principles regarding learning algorithms for deep architectures, in particular those exploiting as building blocks unsupervised learning of single-layer models such as Restricted Boltzmann Machines, used to construct deeper models such as Deep Belief Networks.
Book Synopsis Multicomputer Vision by : S. Levialdi
Download or read book Multicomputer Vision written by S. Levialdi and published by Elsevier. This book was released on 1988-01-01 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multicomputer Vision is a collection of papers and discussions presented at the 8th Workshop on Multicomputers, held in Rome, Italy on June 2-5, 1987. Contributors present multicomputer algorithms for image processing, evaluation and suggestions on multicomputer systems, and new designs in advanced architectures for computer vision. Separating 12 papers into chapters, this book first describes a pyramidal algorithm for image segmentation based on the definition of the “bimean of a population. It then examines the use of Polymorphic Torus architecture to yield positive results in the computation of Hough Transform through executing mesh and tree algorithms. The succeeding papers present the five-level quad-tree pyramid algorithm based on chips from the MPP machine and the algorithm databases required for scheduling and reconfiguration decisions based on the user’s task definition. Other chapters oriented towards the evaluation of multicomputer systems are also provided. These chapters include discussions on multi-processor architectures based on perceptual tasks, the advantages of fine grain associative string structure for general purpose computer vision system, and the use of identical single processor elements for comparison between processor arrays and pipeline computers. The book also contains papers oriented on the design features of new multiprocessor architectures. These papers discuss the memory limitations of parallel machines and the physical realization of a one-dimensional array of 128 to 1024 identical processors. This book provides an informal frame of reference to researchers who are interested in the design and development of algorithms, and architectures or languages of multiprocessor systems.
Book Synopsis Multicomputer Architectures for Artificial Intelli Gence: Toward Fast Robust Parallel Systems by : Uhr
Download or read book Multicomputer Architectures for Artificial Intelli Gence: Toward Fast Robust Parallel Systems written by Uhr and published by . This book was released on 2002-10-01 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Parallel Computation and Computers for Artificial Intelligence by : J.S. Kowalik
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 Computing written by D.J Evans and published by CRC Press. This book was released on 2020-11-25 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Parallel Computing: Methods, Algorithms and Applications presents a collection of original papers presented at the international meeting on parallel processing, methods, algorithms, and applications at Verona, Italy in September 1989.
Author :Jose G. Delgado-Frias Publisher :Springer Science & Business Media ISBN 13 :1461316197 Total Pages :285 pages Book Rating :4.4/5 (613 download)
Book Synopsis VLSI for Artificial Intelligence by : Jose G. Delgado-Frias
Download or read book VLSI for Artificial Intelligence written by Jose G. Delgado-Frias and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Deep Learning Systems by : Andres Rodriguez
Download or read book Deep Learning Systems written by Andres Rodriguez and published by Springer Nature. This book was released on 2022-05-31 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes deep learning systems: the algorithms, compilers, and processor components to efficiently train and deploy deep learning models for commercial applications. The exponential growth in computational power is slowing at a time when the amount of compute consumed by state-of-the-art deep learning (DL) workloads is rapidly growing. Model size, serving latency, and power constraints are a significant challenge in the deployment of DL models for many applications. Therefore, it is imperative to codesign algorithms, compilers, and hardware to accelerate advances in this field with holistic system-level and algorithm solutions that improve performance, power, and efficiency. Advancing DL systems generally involves three types of engineers: (1) data scientists that utilize and develop DL algorithms in partnership with domain experts, such as medical, economic, or climate scientists; (2) hardware designers that develop specialized hardware to accelerate the components in the DL models; and (3) performance and compiler engineers that optimize software to run more efficiently on a given hardware. Hardware engineers should be aware of the characteristics and components of production and academic models likely to be adopted by industry to guide design decisions impacting future hardware. Data scientists should be aware of deployment platform constraints when designing models. Performance engineers should support optimizations across diverse models, libraries, and hardware targets. The purpose of this book is to provide a solid understanding of (1) the design, training, and applications of DL algorithms in industry; (2) the compiler techniques to map deep learning code to hardware targets; and (3) the critical hardware features that accelerate DL systems. This book aims to facilitate co-innovation for the advancement of DL systems. It is written for engineers working in one or more of these areas who seek to understand the entire system stack in order to better collaborate with engineers working in other parts of the system stack. The book details advancements and adoption of DL models in industry, explains the training and deployment process, describes the essential hardware architectural features needed for today's and future models, and details advances in DL compilers to efficiently execute algorithms across various hardware targets. Unique in this book is the holistic exposition of the entire DL system stack, the emphasis on commercial applications, and the practical techniques to design models and accelerate their performance. The author is fortunate to work with hardware, software, data scientist, and research teams across many high-technology companies with hyperscale data centers. These companies employ many of the examples and methods provided throughout the book.
Author :Jose G. Delgado-Frias Publisher :Springer Science & Business Media ISBN 13 :1461537525 Total Pages :411 pages Book Rating :4.4/5 (615 download)
Book Synopsis VLSI for Artificial Intelligence and Neural Networks by : Jose G. Delgado-Frias
Download or read book VLSI for Artificial Intelligence and Neural Networks written by Jose G. Delgado-Frias and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Modern Big Data Architectures by : Dominik Ryzko
Download or read book Modern Big Data Architectures written by Dominik Ryzko and published by John Wiley & Sons. This book was released on 2020-04-09 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides an up-to-date analysis of big data and multi-agent systems The term Big Data refers to the cases, where data sets are too large or too complex for traditional data-processing software. With the spread of new concepts such as Edge Computing or the Internet of Things, production, processing and consumption of this data becomes more and more distributed. As a result, applications increasingly require multiple agents that can work together. A multi-agent system (MAS) is a self-organized computer system that comprises multiple intelligent agents interacting to solve problems that are beyond the capacities of individual agents. Modern Big Data Architectures examines modern concepts and architecture for Big Data processing and analytics. This unique, up-to-date volume provides joint analysis of big data and multi-agent systems, with emphasis on distributed, intelligent processing of very large data sets. Each chapter contains practical examples and detailed solutions suitable for a wide variety of applications. The author, an internationally-recognized expert in Big Data and distributed Artificial Intelligence, demonstrates how base concepts such as agent, actor, and micro-service have reached a point of convergence—enabling next generation systems to be built by incorporating the best aspects of the field. This book: Illustrates how data sets are produced and how they can be utilized in various areas of industry and science Explains how to apply common computational models and state-of-the-art architectures to process Big Data tasks Discusses current and emerging Big Data applications of Artificial Intelligence Modern Big Data Architectures: A Multi-Agent Systems Perspective is a timely and important resource for data science professionals and students involved in Big Data analytics, and machine and artificial learning.
Book Synopsis Domain-Specific Computer Architectures for Emerging Applications by : Chao Wang
Download or read book Domain-Specific Computer Architectures for Emerging Applications written by Chao Wang and published by CRC Press. This book was released on 2024-06-04 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the end of Moore’s Law, domain-specific architecture (DSA) has become a crucial mode of implementing future computing architectures. This book discusses the system-level design methodology of DSAs and their applications, providing a unified design process that guarantees functionality, performance, energy efficiency, and real-time responsiveness for the target application. DSAs often start from domain-specific algorithms or applications, analyzing the characteristics of algorithmic applications, such as computation, memory access, and communication, and proposing the heterogeneous accelerator architecture suitable for that particular application. This book places particular focus on accelerator hardware platforms and distributed systems for various novel applications, such as machine learning, data mining, neural networks, and graph algorithms, and also covers RISC-V open-source instruction sets. It briefly describes the system design methodology based on DSAs and presents the latest research results in academia around domain-specific acceleration architectures. Providing cutting-edge discussion of big data and artificial intelligence scenarios in contemporary industry and typical DSA applications, this book appeals to industry professionals as well as academicians researching the future of computing in these areas.
Book Synopsis Computational Architectures Integrating Neural and Symbolic Processes by : Ron Sun
Download or read book Computational Architectures Integrating Neural and Symbolic Processes written by Ron Sun and published by Springer. This book was released on 2007-08-19 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Architectures Integrating Neural and Symbolic Processes: A Perspective on the State of the Art focuses on a currently emerging body of research. With the reemergence of neural networks in the 1980s with their emphasis on overcoming some of the limitations of symbolic AI, there is clearly a need to support some form of high-level symbolic processing in connectionist networks. As argued by many researchers, on both the symbolic AI and connectionist sides, many cognitive tasks, e.g. language understanding and common sense reasoning, seem to require high-level symbolic capabilities. How these capabilities are realized in connectionist networks is a difficult question and it constitutes the focus of this book. Computational Architectures Integrating Neural and Symbolic Processes addresses the underlying architectural aspects of the integration of neural and symbolic processes. In order to provide a basis for a deeper understanding of existing divergent approaches and provide insight for further developments in this field, this book presents: (1) an examination of specific architectures (grouped together according to their approaches), their strengths and weaknesses, why they work, and what they predict, and (2) a critique/comparison of these approaches. Computational Architectures Integrating Neural and Symbolic Processes is of interest to researchers, graduate students, and interested laymen, in areas such as cognitive science, artificial intelligence, computer science, cognitive psychology, and neurocomputing, in keeping up-to-date with the newest research trends. It is a comprehensive, in-depth introduction to this new emerging field.
Book Synopsis Artificial Intelligence Methods And Applications by : Nikolas G Bourbakis
Download or read book Artificial Intelligence Methods And Applications written by Nikolas G Bourbakis and published by World Scientific. This book was released on 1992-12-31 with total page 740 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is the first in a series which deals with the challenge of AI issues, gives updates of AI methods and applications, and promotes high quality new ideas, techniques and methodologies in AI. This volume contains articles by 38 specialists in various AI subfields covering theoretical and application issues.
