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Author: Vivek Kale
Publisher: CRC Press
ISBN: 1351029207
Category : Computers
Languages : en
Pages : 330
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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.
Author: Vivek Kale
Publisher: CRC Press
ISBN: 1351029207
Category : Computers
Languages : en
Pages : 330
Get Book Here
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.
Author: Christian Bischof
Publisher: IOS Press
ISBN: 158603796X
Category : Computers
Languages : en
Pages : 824
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Book Description
ParCo2007 marks a quarter of a century of the international conferences on parallel computing that started in Berlin in 1983. The aim of the conference is to give an overview of the developments, applications and future trends in high-performance computing for various platforms.
Author: Vivek Kale
Publisher: CRC Press
ISBN: 1351029215
Category : Computers
Languages : en
Pages : 380
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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.
Author: BASU, S. K.
Publisher: PHI Learning Pvt. Ltd.
ISBN: 8120352122
Category : Computers
Languages : en
Pages : 408
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Book Description
This concise text is designed to present the recent advances in parallel and distributed architectures and algorithms within an integrated framework. Beginning with an introduction to the basic concepts, the book goes on discussing the basic methods of parallelism exploitation in computation through vector processing, super scalar and VLIW processing, array processing, associative processing, systolic algorithms, and dataflow computation. After introducing interconnection networks, it discusses parallel algorithms for sorting, Fourier transform, matrix algebra, and graph theory. The second part focuses on basics and selected theoretical issues of distributed processing. Architectures and algorithms have been dealt in an integrated way throughout the book. The last chapter focuses on the different paradigms and issues of high performance computing making the reading more interesting. This book is meant for the senior level undergraduate and postgraduate students of computer science and engineering, and information technology. The book is also useful for the postgraduate students of computer science and computer application.
Author: V. Rajaraman,
Publisher: PHI Learning Pvt. Ltd.
ISBN: 8120352629
Category : Computers
Languages : en
Pages : 493
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Book Description
Today all computers, from tablet/desktop computers to super computers, work in parallel. A basic knowledge of the architecture of parallel computers and how to program them, is thus, essential for students of computer science and IT professionals. In its second edition, the book retains the lucidity of the first edition and has added new material to reflect the advances in parallel computers. It is designed as text for the final year undergraduate students of computer science and engineering and information technology. It describes the principles of designing parallel computers and how to program them. This second edition, while retaining the general structure of the earlier book, has added two new chapters, ‘Core Level Parallel Processing’ and ‘Grid and Cloud Computing’ based on the emergence of parallel computers on a single silicon chip popularly known as multicore processors and the rapid developments in Cloud Computing. All chapters have been revised and some chapters are re-written to reflect the emergence of multicore processors and the use of MapReduce in processing vast amounts of data. The new edition begins with an introduction to how to solve problems in parallel and describes how parallelism is used in improving the performance of computers. The topics discussed include instruction level parallel processing, architecture of parallel computers, multicore processors, grid and cloud computing, parallel algorithms, parallel programming, compiler transformations, operating systems for parallel computers, and performance evaluation of parallel computers.
Author: J. J. Dongarra
Publisher: North Holland
ISBN:
Category : Computers
Languages : en
Pages : 328
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Book Description
Computer Systems Organization -- Parallel architecture.
Author: David B. Kirk
Publisher: Newnes
ISBN: 0123914183
Category : Computers
Languages : en
Pages : 519
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Book Description
Programming Massively Parallel Processors: A Hands-on Approach, Second Edition, teaches students how to program massively parallel processors. It offers a detailed discussion of various techniques for constructing parallel programs. Case studies are used to demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs. This guide shows both student and professional alike the basic concepts of parallel programming and GPU architecture. Topics of performance, floating-point format, parallel patterns, and dynamic parallelism are covered in depth. This revised edition contains more parallel programming examples, commonly-used libraries such as Thrust, and explanations of the latest tools. It also provides new coverage of CUDA 5.0, improved performance, enhanced development tools, increased hardware support, and more; increased coverage of related technology, OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelism; and two new case studies (on MRI reconstruction and molecular visualization) that explore the latest applications of CUDA and GPUs for scientific research and high-performance computing. This book should be a valuable resource for advanced students, software engineers, programmers, and hardware engineers. New coverage of CUDA 5.0, improved performance, enhanced development tools, increased hardware support, and more Increased coverage of related technology, OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelism Two new case studies (on MRI reconstruction and molecular visualization) explore the latest applications of CUDA and GPUs for scientific research and high-performance computing
Author: Janusz Kowalik
Publisher: IOS Press
ISBN: 1614990298
Category : Computers
Languages : en
Pages : 312
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Book Description
Author: Fayez Gebali
Publisher: John Wiley & Sons
ISBN: 0470934638
Category : Computers
Languages : en
Pages : 372
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Book Description
There is a software gap between the hardware potential and the performance that can be attained using today's software parallel program development tools. The tools need manual intervention by the programmer to parallelize the code. Programming a parallel computer requires closely studying the target algorithm or application, more so than in the traditional sequential programming we have all learned. The programmer must be aware of the communication and data dependencies of the algorithm or application. This book provides the techniques to explore the possible ways to program a parallel computer for a given application.
Author: Peter Pacheco
Publisher: Morgan Kaufmann
ISBN: 012804618X
Category : Computers
Languages : en
Pages : 498
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Book Description
An Introduction to Parallel Programming, Second Edition presents a tried-and-true tutorial approach that shows students how to develop effective parallel programs with MPI, Pthreads and OpenMP.As the first undergraduate text to directly address compiling and running parallel programs on multi-core and cluster architecture, this second edition carries forward its clear explanations for designing, debugging and evaluating the performance of distributed and shared-memory programs while adding coverage of accelerators via new content on GPU programming and heterogeneous programming. New and improved user-friendly exercises teach students how to compile, run and modify example programs. Takes a tutorial approach, starting with small programming examples and building progressively to more challenging examples Explains how to develop parallel programs using MPI, Pthreads and OpenMP programming models A robust package of online ancillaries for instructors and students includes lecture slides, solutions manual, downloadable source code, and an image bank New to this edition: New chapters on GPU programming and heterogeneous programming New examples and exercises related to parallel algorithms
