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Download and Read online Parallel Computer Architecture ebooks in PDF, epub, Tuebl Mobi, Kindle Book. Get Free Parallel Computer Architecture Textbook and unlimited access to our library by created an account. Fast Download speed and ads Free!

Parallel Computer Architecture

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.

Parallel Computer Architecture

The most exciting development in parallel computer architecture is the convergence of traditionally disparate approaches on a common machine structure. This book explains the forces behind this convergence of shared-memory, message-passing, data parallel, and data-driven computing architectures. It then examines the design issues that are critical to all parallel architecture across the full range of modern design, covering data access, communication performance, coordination of cooperative work, and correct implementation of useful semantics. It not only describes the hardware and software techniques for addressing each of these issues but also explores how these techniques interact in the same system. Examining architecture from an application-driven perspective, it provides comprehensive discussions of parallel programming for high performance and of workload-driven evaluation, based on understanding hardware-software interactions. synthesizes a decade of research and development for practicing engineers, graduate students, and researchers in parallel computer architecture, system software, and applications development presents in-depth application case studies from computer graphics, computational science and engineering, and data mining to demonstrate sound quantitative evaluation of design trade-offs describes the process of programming for performance, including both the architecture-independent and architecture-dependent aspects, with examples and case-studies illustrates bus-based and network-based parallel systems with case studies of more than a dozen important commercial designs

PARALLEL COMPUTERS ARCHITECTURE AND PROGRAMMING

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.

Parallel Computers 2

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.

Parallel Computer Organization and Design

A design-oriented text for advanced computer architecture courses, covering parallelism, complexity, power, reliability and performance.

Fundamentals of Parallel Computer Architecture

Microprogrammable Parallel Computer

This book takes up the challenge offered by recent advances in theoretical computer science and artificial intelligence that have created a demand for a radically different type of computer architecture. It demonstrates the possibility of register transfer level parallel computing with microprogrammable flexible architecture that can fulfill a wide variety of user requirements, and provides all the necessary technical information to understand the process of design, development, and evaluation of this innovative MUNAP computer.After introducing the basic concepts in the computer architecture and microprogramming area, the book describes how the architect goes about selecting microoperations, considering software/firmware/hardware tradeoffs and what schemes might be used for interleaved memory access and interconnection network. Microprogrammed computer models are defined for the evaluation of computers with similar architectures.Microprogrammable Parallel Computer presents the results of exhaustive experimentations with this architecture showing how it can be exploited in current research on emulation of a machine language, tagged architectures, language processing for Smalltalk-80 and Prolog, software testing, database systems, 3D graphics, and numerical computation.Contents: Introduction. Design Principle. Basic Organization. Preliminary Evaluation. Hardware Development. Firmware Development. Applications. Architectural Evaluation and Improvement. Future Directions.Takanobu Baba is an Associate Professor, Department of Information Science, Utsunomiya University, Japan. Microprogrammable Parallel Computer is included in the Computer Systems Series, edited by Herb Schwetman.

Novel Parallel Computer Architecture and Some Applications

Advanced Computer Architecture and Parallel Processing

Computer architecture deals with the physical configuration, logical structure, formats, protocols, and operational sequences for processing data, controlling the configuration, and controlling the operations over a computer. It also encompasses word lengths, instruction codes, and the interrelationships among the main parts of a computer or group of computers. This two-volume set offers a comprehensive coverage of the field of computer organization and architecture.

Scalable Parallel Computing

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.

Architectural Development Tracks in Parallel Computing

Introduction to Parallel Processing

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.

Bioinformatics

New sequencing technologies have broken many experimental barriers to genome scale sequencing, leading to the extraction of huge quantities of sequence data. This expansion of biological databases established the need for new ways to harness and apply the astounding amount of available genomic information and convert it into substantive biological understanding. A complilation of recent approaches from prominent researchers, Bioinformatics: High Performance Parallel Computer Architectures discusses how to take advantage of bioinformatics applications and algorithms on a variety of modern parallel architectures. Two factors continue to drive the increasing use of modern parallel computer architectures to address problems in computational biology and bioinformatics: high-throughput techniques for DNA sequencing and gene expression analysis—which have led to an exponential growth in the amount of digital biological data—and the multi- and many-core revolution within computer architecture. Presenting key information about how to make optimal use of parallel architectures, this book: Describes algorithms and tools including pairwise sequence alignment, multiple sequence alignment, BLAST, motif finding, pattern matching, sequence assembly, hidden Markov models, proteomics, and evolutionary tree reconstruction Addresses GPGPU technology and the associated massively threaded CUDA programming model Reviews FPGA architecture and programming Presents several parallel algorithms for computing alignments on the Cell/BE architecture, including linear-space pairwise alignment, syntenic alignment, and spliced alignment Assesses underlying concepts and advances in orchestrating the phylogenetic likelihood function on parallel computer architectures (ranging from FPGAs upto the IBM BlueGene/L supercomputer) Covers several effective techniques to fully exploit the computing capability of many-core CUDA-enabled GPUs to accelerate protein sequence database searching, multiple sequence alignment, and motif finding Explains a parallel CUDA-based method for correcting sequencing base-pair errors in HTSR data Because the amount of publicly available sequence data is growing faster than single processor core performance speed, modern bioinformatics tools need to take advantage of parallel computer architectures. Now that the era of the many-core processor has begun, it is expected that future mainstream processors will be parallel systems. Beneficial to anyone actively involved in research and applications, this book helps you to get the most out of these tools and create optimal HPC solutions for bioinformatics.

Experimental Parallel Computing Architectures

Computer Systems Organization -- Parallel architecture.

Parallel Computing Architectures and APIs

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.

Computer Architecture

Computer Architecture/Software Engineering

Distributed Parallel Computing Architecture for Monitoring and Control of Large Physical Processes

Parallel Computing Works

A clear illustration of how parallel computers can be successfully applied to large-scale scientific computations. This book demonstrates how a variety of applications in physics, biology, mathematics and other sciences were implemented on real parallel computers to produce new scientific results. It investigates issues of fine-grained parallelism relevant for future supercomputers with particular emphasis on hypercube architecture. The authors describe how they used an experimental approach to configure different massively parallel machines, design and implement basic system software, and develop algorithms for frequently used mathematical computations. They also devise performance models, measure the performance characteristics of several computers, and create a high-performance computing facility based exclusively on parallel computers. By addressing all issues involved in scientific problem solving, Parallel Computing Works! provides valuable insight into computational science for large-scale parallel architectures. For those in the sciences, the findings reveal the usefulness of an important experimental tool. Anyone in supercomputing and related computational fields will gain a new perspective on the potential contributions of parallelism. Includes over 30 full-color illustrations.

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Introduction to Parallel Computing

Introduction to Parallel Computing provides an in-depth look at techniques for the design and analysis of parallel algorithms and for programming these algorithms on commercially available parallel platforms. The book discusses principles of parallel algorithm design and different parallel programming models with extensive coverage of MPI, POSIX threads, and OpenMP. It provides a broad and balanced coverage of various core topics such as sorting, graph algorithms, discrete optimization techniques, data-mining algorithms, and a number of algorithms used in numerical and scientific computing applications. The basic approach advocated in this text is one of portable parallel algorithm and software development, an empahsis lacking in all existing textbooks on parallel computing. To enhance the pedagogical value of the text, extensive examples, diagrams, exercises of varying degrees of difficulty, and bibliographical remarks are provided. In addition to serving as a textbook and a reference source for professionals and parallel software developers, the book will help students and researchers in non computer-science disciplines who need to solve computation-intensive problems using parallel computers.

PARALLEL COMPUTERS

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.

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