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Thursday, April 30, 2015

Download computer architecture and parallel computing EBooks | Read online computer architecture and parallel computing EBooks

Download computer architecture and parallel computing EBooks | Read online computer architecture and parallel computing EBooks




Advanced Computer Architecture and Parallel Processing,

by Hesham El-Rewini
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Parallel Computer Architecture,A Hardware/software Approach
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.
by David E. Culler
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Computer Architecture and Parallel Processing,

by Kai Hwang
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Scalable Parallel Computing,Technology, Architecture, Programming
This comprehensive new text from author Kai Hwang covers four important aspects of parallel and distributed computing -- principles, technology, architecture, and programming -- and can be used for several upper-level courses.
by Kai Hwang
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Computer Architecture and Parallel Processing,

by Bharat Bhushan Agarwal
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Advanced Computer Architecture and Computing,

by S.S.Jadhav
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PARALLEL COMPUTERS,ARCHITECTURE AND PROGRAMMING
Today, parallel computing arouses enormous interest among students and professionals as it is clear that, as the new millennium progresses, all computers will work in parallel. A basic knowledge of the design and use of parallel computers is, therefore, essential for both students of computing and users of computers.Designed as an introductory-level textbook for the final year undergraduate students of computer science and engineering, this well-organized book covers state-of-the-art principles and techniques for designing and programming parallel computers. In the process, Professor Rajaraman and Dr. Siva Ram Murthy, with their wealth of knowledge and years of teaching and research experience, give a masterly analysis of the various aspects of parallel computing.The book begins with an introduction to the current state and developments in parallel computing, then it goes on to give a detailed discussion on such topics as instruction level parallel processing, architecture of parallel computers, parallel algorithms and parallel programming. Besides, the book gives an in-depth coverage of compiler transformations and operating systems for parallel computers. The text concludes with a chapter on performance evaluation of parallel computers.Interspersed with copious examples and numerous exercises, this timely book should prove to be a handy and treasured volume for students as well as professionals.
by V. RAJARAMAN
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Programming Massively Parallel Processors,A Hands-on Approach
Programming Massively Parallel Processors: A Hands-on Approach shows both student and professional alike the basic concepts of parallel programming and GPU architecture. Various techniques for constructing parallel programs are explored in detail. Case studies demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs. Topics of performance, floating-point format, parallel patterns, and dynamic parallelism are covered in depth. This best-selling guide to CUDA and GPU parallel programming has been revised with more parallel programming examples, commonly-used libraries such as Thrust, and explanations of the latest tools. With these improvements, the book retains its concise, intuitive, practical approach based on years of road-testing in the authors' own parallel computing courses. Updates in this new edition include: 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
by David B. Kirk
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Network-Based Parallel Computing - Communication, Architecture, and Applications,4th International Workshop, CANPC 2000 Toulouse, France, January 8, 2000 Proceedings
Clusters of workstations/PCs connected by o?-the-shelf networks have become popular as platforms for cost-e?ective parallel computing. Technological - vances in both hardware and software have made such a network-based parallel computingplatform an a?ordable alternative to commercial supercomputers for an increasing number of scienti?c applications. Continuing in the tradition of the three previously successful workshops, this fourth Workshop on Communication, Architecture and Applications for Network-basedParallelComputing(CANPC 2000)broughttogetherresearchers and practitioners working in architecture, system software, applications, and performance evaluation to discuss state-of-the-art solutions for network-based parallel computing. This year, the workshop was held in conjunction with the sixth International Symposium on High-Performance Computer Architecture (HPCA-6). As in prior editions, the papers presented here are representative of a sp- trum of research e?orts from groups in academia and industry to further - prove cluster computing s viability, performance, cost-e?ectiveness, and usab- ity. Speci?cally, we have arranged the contributions in this edition into four groups: (1) program development and execution support, (2) network router - chitecture, (3) system support for communication abstractions, and (4) network software and interface architecture."
by Babak Falsafi
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Parallel Computers 2,Architecture, Programming and Algorithms
Since the publication of the first edition, parallel computing technology has gained considerable momentum. A large proportion of this has come from the improvement in VLSI techniques, offering one to two orders of magnitude more devices than previously possible. A second contributing factor in the fast development of the subject is commercialization. The supercomputer is no longer restricted to a few well-established research institutions and large companies. A new computer breed combining the architectural advantages of the supercomputer with the advance of VLSI technology is now available at very attractive prices. A pioneering device in this development is the transputer, a VLSI processor specifically designed to operate in large concurrent systems. Parallel Computers 2: Architecture, Programming and Algorithms reflects the shift in emphasis of parallel computing and tracks the development of supercomputers in the years since the first edition was published. It looks at large-scale parallelism as found in transputer ensembles. This extensively rewritten second edition includes major new sections on the transputer and the OCCAM language. The book contains specific information on the various types of machines available, details of computer architecture and technologies, and descriptions of programming languages and algorithms. Aimed at an advanced undergraduate and postgraduate level, this handbook is also useful for research workers, machine designers, and programmers concerned with parallel computers. In addition, it will serve as a guide for potential parallel computer users, especially in disciplines where large amounts of computer time are regularly used.
by R.W Hockney
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Parallel Programming,for Multicore and Cluster Systems
Innovations in hardware architecture, like hyper-threading or multicore processors, mean that parallel computing resources are available for inexpensive desktop computers. In only a few years, many standard software products will be based on concepts of parallel programming implemented on such hardware, and the range of applications will be much broader than that of scientific computing, up to now the main application area for parallel computing. Rauber and Rünger take up these recent developments in processor architecture by giving detailed descriptions of parallel programming techniques that are necessary for developing efficient programs for multicore processors as well as for parallel cluster systems and supercomputers. Their book is structured in three main parts, covering all areas of parallel computing: the architecture of parallel systems, parallel programming models and environments, and the implementation of efficient application algorithms. The emphasis lies on parallel programming techniques needed for different architectures. For this second edition, all chapters have been carefully revised. The chapter on architecture of parallel systems has been updated considerably, with a greater emphasis on the architecture of multicore systems and adding new material on the latest developments in computer architecture. Lastly, a completely new chapter on general-purpose GPUs and the corresponding programming techniques has been added. The main goal of the book is to present parallel programming techniques that can be used in many situations for a broad range of application areas and which enable the reader to develop correct and efficient parallel programs. Many examples and exercises are provided to show how to apply the techniques. The book can be used as both a textbook for students and a reference book for professionals. The material presented has been used for courses in parallel programming at different universities for many years.
by Thomas Rauber
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Parallel Processing and Parallel Algorithms,Theory and Computation
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.
by Seyed H Roosta
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Introduction to Parallel Processing,Algorithms and Architectures
THE CONTEXT OF PARALLEL PROCESSING The field of digital computer architecture has grown explosively in the past two decades. Through a steady stream of experimental research, tool-building efforts, and theoretical studies, the design of an instruction-set architecture, once considered an art, has been transformed into one of the most quantitative branches of computer technology. At the same time, better understanding of various forms of concurrency, from standard pipelining to massive parallelism, and invention of architectural structures to support a reasonably efficient and user-friendly programming model for such systems, has allowed hardware performance to continue its exponential growth. This trend is expected to continue in the near future. This explosive growth, linked with the expectation that performance will continue its exponential rise with each new generation of hardware and that (in stark contrast to software) computer hardware will function correctly as soon as it comes off the assembly line, has its down side. It has led to unprecedented hardware complexity and almost intolerable dev- opment costs. The challenge facing current and future computer designers is to institute simplicity where we now have complexity; to use fundamental theories being developed in this area to gain performance and ease-of-use benefits from simpler circuits; to understand the interplay between technological capabilities and limitations, on the one hand, and design decisions based on user and application requirements on the other.
by Behrooz Parhami
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INTRODUCTION TO PARALLEL PROCESSING,
From the days of vacuum tubes, today's computers have come a long way in CPU power. Order of magnitude increase in computational power is now being realized using the technology of parallel processing. The area of parallel processing is exciting, challenging and, perhaps, intimidating. This compact and lucidly written book gives the readers an overview of parallel processing, exploring the interesting landmarks in detail and providing them with sufficient practical exposure to the programming issues. This enables them to make realistic attempts at writing parallel programs using the available software tools. The book systematically covers such topics as shared memory programming using threads and processes, distributed memory programming using PVM and RPC, data dependency analysis, parallel algorithms, parallel programming languages, distributed data-bases and operating systems, and debugging of parallel programs. It is an ideal textbook for courses on parallel programming at the undergraduate and postgraduate levels. It will also be useful for computer professionals interested in exploring the field of parallel computing.
by P. RAVI PRAKASH
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Encyclopedia of Parallel Computing,
This Encyclopedia covers machine organization, programming, algorithms, and applications. Within each topic area, the Encyclopedia covers concepts, designs, and specific implementations. The primary sections include Algorithms; Architecture; Software and more.
by David Padua
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