Parallel Architectures for Data/knowledge-based Systems

Parallel Architectures for Data/knowledge-based Systems PDF Author: L. L. Miller
Publisher:
ISBN:
Category : Computers
Languages : en
Pages : 624

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Parallel Architectures for Data/knowledge-based Systems

Parallel Architectures for Data/knowledge-based Systems PDF Author: L. L. Miller
Publisher:
ISBN:
Category : Computers
Languages : en
Pages : 624

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Emerging Trends in Database and Knowledge Based Machines

Emerging Trends in Database and Knowledge Based Machines PDF Author: Mahdi Abdelguerfi
Publisher: Wiley-IEEE Computer Society Press
ISBN:
Category : Computers
Languages : en
Pages : 320

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Book Description
Parallel database and knowledge-base systems; IDIOMS: a multitransputer database machine; From DBC to MDBS - progression in database machine research; Rinda: a relational database processor for large databases; Using massively-parallel general computing platforms for DBMS; Knowledge-base machines.

Unconventional Computer Architectures

Unconventional Computer Architectures PDF Author: A. R. Hurson
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Parallel Computing Architectures and APIs

Parallel Computing Architectures and APIs PDF Author: Vivek Kale
Publisher: CRC Press
ISBN: 1351029215
Category : Computers
Languages : en
Pages : 407

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Book Description
Parallel Computing Architectures and APIs: IoT Big Data Stream Processing commences from the point high-performance uniprocessors were becoming increasingly complex, expensive, and power-hungry. A basic trade-off exists between the use of one or a small number of such complex processors, at one extreme, and a moderate to very large number of simpler processors, at the other. When combined with a high-bandwidth, interprocessor communication facility leads to significant simplification of the design process. However, two major roadblocks prevent the widespread adoption of such moderately to massively parallel architectures: the interprocessor communication bottleneck, and the difficulty and high cost of algorithm/software development. One of the most important reasons for studying parallel computing architectures is to learn how to extract the best performance from parallel systems. Specifically, you must understand its architectures so that you will be able to exploit those architectures during programming via the standardized APIs. This book would be useful for analysts, designers and developers of high-throughput computing systems essential for big data stream processing emanating from IoT-driven cyber-physical systems (CPS). This pragmatic book: Devolves uniprocessors in terms of a ladder of abstractions to ascertain (say) performance characteristics at a particular level of abstraction Explains limitations of uniprocessor high performance because of Moore’s Law Introduces basics of processors, networks and distributed systems Explains characteristics of parallel systems, parallel computing models and parallel algorithms Explains the three primary categorical representatives of parallel computing architectures, namely, shared memory, message passing and stream processing Introduces the three primary categorical representatives of parallel programming APIs, namely, OpenMP, MPI and CUDA Provides an overview of Internet of Things (IoT), wireless sensor networks (WSN), sensor data processing, Big Data and stream processing Provides introduction to 5G communications, Edge and Fog computing Parallel Computing Architectures and APIs: IoT Big Data Stream Processing discusses stream processing that enables the gathering, processing and analysis of high-volume, heterogeneous, continuous Internet of Things (IoT) big data streams, to extract insights and actionable results in real time. Application domains requiring data stream management include military, homeland security, sensor networks, financial applications, network management, web site performance tracking, real-time credit card fraud detection, etc.

Parallel, Object-Oriented, and Active Knowledge Base Systems

Parallel, Object-Oriented, and Active Knowledge Base Systems PDF Author: Ioannis Vlahavas
Publisher: Springer Science & Business Media
ISBN: 9780792381174
Category : Computers
Languages : en
Pages : 176

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Book Description
Knowledge Base Systems are an integration of conventional database systems with Artificial Intelligence techniques. They provide inference capabilities to the database system by encapsulating the knowledge of the application domain within the database. Knowledge is the most valuable of all corporate resources that must be captured, stored, re-used and continuously improved, in much the same way as database systems were important in the previous decade. Flexible, extensible, and yet efficient Knowledge Base Systems are needed to capture the increasing demand for knowledge-based applications which will become a significant market in the next decade. Knowledge can be expressed in many static and dynamic forms; the most prominent being domain objects, their relationships, and their rules of evolution and transformation. It is important to express and seamlessly use all types of knowledge in a single Knowledge Base System. Parallel, Object-Oriented, and Active Knowledge Base Systems presents in detail features that a Knowledge Base System should have in order to fulfill the above requirements. Parallel, Object-Oriented, and Active Knowledge Base Systems covers in detail the following topics: Integration of deductive, production, and active rules in sequential database systems. Integration and inter-operation of multiple rule types into the same Knowledge Base System. Parallel rule matching and execution, for deductive, production, and active rules, in parallel Export, Knowledge Base, and Database Systems. In-depth description of a Parallel, Object-Oriented, and Active Knowledge Base System that integrates all rule paradigms into a single database system without hindering performance. Parallel, Object-Oriented, and Active Knowledge Base Systems is intended as a graduate-level text for a course on Knowledge Base Systems and as a reference for researchers and practitioners in the areas of database systems, knowledge base systems and Artificial Intelligence.

Emerging Trends in Database and Knowledge-base Machines

Emerging Trends in Database and Knowledge-base Machines PDF Author: Mahdi Abdelguerfi
Publisher:
ISBN: 9780818665509
Category : Database management
Languages : en
Pages : 302

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Book Description
This book illustrates interesting ways in which new parallel hardware is being used to improve performance and increase functionality for a variety of information systems. The book, containing 13 original papers, surveys the latest trends in performance enhancing architectures for smart information systems. It will appeal to all those engaged in the design or use of high-performance architectures for non-numeric applications. The machines featured throughout this text are designed to support information systems ranging from relational databases to semantic networks and other artificial intelligence paradigms. In addition, many of the projects illustrated in the book contain generic architectural ideas that support higher-level requirements and are based on semantics-free hardware designs.

Deep Learning and Parallel Computing Environment for Bioengineering Systems

Deep Learning and Parallel Computing Environment for Bioengineering Systems PDF Author: Arun Kumar Sangaiah
Publisher: Academic Press
ISBN: 0128172932
Category : Technology & Engineering
Languages : en
Pages : 282

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Book Description
Deep Learning and Parallel Computing Environment for Bioengineering Systems delivers a significant forum for the technical advancement of deep learning in parallel computing environment across bio-engineering diversified domains and its applications. Pursuing an interdisciplinary approach, it focuses on methods used to identify and acquire valid, potentially useful knowledge sources. Managing the gathered knowledge and applying it to multiple domains including health care, social networks, mining, recommendation systems, image processing, pattern recognition and predictions using deep learning paradigms is the major strength of this book. This book integrates the core ideas of deep learning and its applications in bio engineering application domains, to be accessible to all scholars and academicians. The proposed techniques and concepts in this book can be extended in future to accommodate changing business organizations' needs as well as practitioners' innovative ideas. - Presents novel, in-depth research contributions from a methodological/application perspective in understanding the fusion of deep machine learning paradigms and their capabilities in solving a diverse range of problems - Illustrates the state-of-the-art and recent developments in the new theories and applications of deep learning approaches applied to parallel computing environment in bioengineering systems - Provides concepts and technologies that are successfully used in the implementation of today's intelligent data-centric critical systems and multi-media Cloud-Big data

Parallel Processing for Artificial Intelligence

Parallel Processing for Artificial Intelligence PDF Author: Laveen N. Kanal
Publisher:
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 452

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Book Description
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 Computing: Technology Trends

Parallel Computing: Technology Trends PDF Author: I. Foster
Publisher: IOS Press
ISBN: 1643680714
Category : Computers
Languages : en
Pages : 806

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Book Description
The year 2019 marked four decades of cluster computing, a history that began in 1979 when the first cluster systems using Components Off The Shelf (COTS) became operational. This achievement resulted in a rapidly growing interest in affordable parallel computing for solving compute intensive and large scale problems. It also directly lead to the founding of the Parco conference series. Starting in 1983, the International Conference on Parallel Computing, ParCo, has long been a leading venue for discussions of important developments, applications, and future trends in cluster computing, parallel computing, and high-performance computing. ParCo2019, held in Prague, Czech Republic, from 10 – 13 September 2019, was no exception. Its papers, invited talks, and specialized mini-symposia addressed cutting-edge topics in computer architectures, programming methods for specialized devices such as field programmable gate arrays (FPGAs) and graphical processing units (GPUs), innovative applications of parallel computers, approaches to reproducibility in parallel computations, and other relevant areas. This book presents the proceedings of ParCo2019, with the goal of making the many fascinating topics discussed at the meeting accessible to a broader audience. The proceedings contains 57 contributions in total, all of which have been peer-reviewed after their presentation. These papers give a wide ranging overview of the current status of research, developments, and applications in parallel computing.

Parallel Computer Architecture

Parallel Computer Architecture PDF Author: David Culler
Publisher: Gulf Professional Publishing
ISBN: 1558603433
Category : Computers
Languages : en
Pages : 1056

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Book Description
This book outlines a set of issues that are critical to all of parallel architecture--communication latency, communication bandwidth, and coordination of cooperative work (across modern designs). It describes the set of techniques available in hardware and in software to address each issues and explore how the various techniques interact.