Skip to main content

Books in Parallel and distributed computing

31-40 of 64 results in All results

Accelerating MATLAB with GPU Computing

  • 1st Edition
  • November 18, 2013
  • Jung W. Suh + 1 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 4 0 8 0 8 0 - 5
  • eBook
    9 7 8 - 0 - 1 2 - 4 0 7 9 1 6 - 8
Beyond simulation and algorithm development, many developers increasingly use MATLAB even for product deployment in computationally heavy fields. This often demands that MATLAB codes run faster by leveraging the distributed parallelism of Graphics Processing Units (GPUs). While MATLAB successfully provides high-level functions as a simulation tool for rapid prototyping, the underlying details and knowledge needed for utilizing GPUs make MATLAB users hesitate to step into it. Accelerating MATLAB with GPUs offers a primer on bridging this gap. Starting with the basics, setting up MATLAB for CUDA (in Windows, Linux and Mac OS X) and profiling, it then guides users through advanced topics such as CUDA libraries. The authors share their experience developing algorithms using MATLAB, C++ and GPUs for huge datasets, modifying MATLAB codes to better utilize the computational power of GPUs, and integrating them into commercial software products. Throughout the book, they demonstrate many example codes that can be used as templates of C-MEX and CUDA codes for readers’ projects. Download example codes from the publisher's website: http://booksite.elsevier.com/9780124080805/

Massively Parallel Processing Applications and Development

  • 1st Edition
  • October 22, 2013
  • L. Dekker + 2 more
  • English
  • eBook
    9 7 8 - 1 - 4 8 3 2 - 9 0 4 3 - 0
The contributions of a diverse selection of international hardware and software specialists are assimilated in this book's exploration of the development of massively parallel processing (MPP). The emphasis is placed on industrial applications and collaboration with users and suppliers from within the industrial community consolidates the scope of the publication.From a practical point of view, massively parallel data processing is a vital step to further innovation in all areas where large amounts of data must be processed in parallel or in a distributed manner, e.g. fluid dynamics, meteorology, seismics, molecular engineering, image processing, parallel data base processing. MPP technology can make the speed of computation higher and substantially reduce the computational costs. However, to achieve these features, the MPP software has to be developed further to create user-friendly programming systems and to become transparent for present-day computer software.Application of novel electro-optic components and devices is continuing and will be a key for much more general and powerful architectures. Vanishing of communication hardware limitations will result in the elimination of programming bottlenecks in parallel data processing. Standardization of the functional characteristics of a programming model of massively parallel computers will become established. Then efficient programming environments can be developed. The result will be a widespread use of massively parallel processing systems in many areas of application.

Cloud Computing

  • 1st Edition
  • May 24, 2013
  • Dan C. Marinescu
  • English
  • eBook
    9 7 8 - 0 - 1 2 - 4 0 4 6 4 1 - 2
Cloud Computing: Theory and Practice provides students and IT professionals with an in-depth analysis of the cloud from the ground up. Beginning with a discussion of parallel computing and architectures and distributed systems, the book turns to contemporary cloud infrastructures, how they are being deployed at leading companies such as Amazon, Google and Apple, and how they can be applied in fields such as healthcare, banking and science. The volume also examines how to successfully deploy a cloud application across the enterprise using virtualization, resource management and the right amount of networking support, including content delivery networks and storage area networks. Developers will find a complete introduction to application development provided on a variety of platforms.

Mastering Cloud Computing

  • 1st Edition
  • April 5, 2013
  • Rajkumar Buyya + 2 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 4 1 1 4 5 4 - 8
  • eBook
    9 7 8 - 0 - 1 2 - 4 0 9 5 3 9 - 7
Mastering Cloud Computing is designed for undergraduate students learning to develop cloud computing applications. Tomorrow's applications won’t live on a single computer but will be deployed from and reside on a virtual server, accessible anywhere, any time. Tomorrow's application developers need to understand the requirements of building apps for these virtual systems, including concurrent programming, high-performance computing, and data-intensive systems. The book introduces the principles of distributed and parallel computing underlying cloud architectures and specifically focuses on virtualization, thread programming, task programming, and map-reduce programming. There are examples demonstrating all of these and more, with exercises and labs throughout.

Intel Xeon Phi Coprocessor High Performance Programming

  • 1st Edition
  • February 11, 2013
  • James Jeffers + 1 more
  • English
  • eBook
    9 7 8 - 0 - 1 2 - 4 1 0 4 9 4 - 5
Authors Jim Jeffers and James Reinders spent two years helping educate customers about the prototype and pre-production hardware before Intel introduced the first Intel Xeon Phi coprocessor. They have distilled their own experiences coupled with insights from many expert customers, Intel Field Engineers, Application Engineers and Technical Consulting Engineers, to create this authoritative first book on the essentials of programming for this new architecture and these new products. This book is useful even before you ever touch a system with an Intel Xeon Phi coprocessor. To ensure that your applications run at maximum efficiency, the authors emphasize key techniques for programming any modern parallel computing system whether based on Intel Xeon processors, Intel Xeon Phi coprocessors, or other high performance microprocessors. Applying these techniques will generally increase your program performance on any system, and better prepare you for Intel Xeon Phi coprocessors and the Intel MIC architecture.

Web Services, Service-Oriented Architectures, and Cloud Computing

  • 2nd Edition
  • December 31, 2012
  • Douglas K. Barry
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 3 9 8 3 5 7 - 2
  • eBook
    9 7 8 - 0 - 1 2 - 4 0 7 2 0 0 - 8
Web Services, Service-Oriented Architectures, and Cloud Computing is a jargon-free, highly illustrated explanation of how to leverage the rapidly multiplying services available on the Internet. The future of business will depend on software agents, mobile devices, public and private clouds, big data, and other highly connected technology. IT professionals will need to evaluate and combine online services into service-oriented architectures (SOA), often depending on Web services and cloud computing. This can mean a fundamental shift away from custom software and towards a more nimble use of semantic vocabularies, middle-tier systems, adapters and other standardizing aspects. This book is a guide for the savvy manager who wants to capitalize on this technological revolution. It begins with a high-level example of how an average person might interact with a service-oriented architecture, and progresses to more detail, discussing technical forces driving adoption and how to manage technology, culture and personnel issues that can arise during adoption. An extensive reference section provides quick access to commonly used terms and concepts.

Computation and Storage in the Cloud

  • 1st Edition
  • December 31, 2012
  • Dong Yuan + 2 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 4 0 7 7 6 7 - 6
  • eBook
    9 7 8 - 0 - 1 2 - 4 0 7 8 7 9 - 6
Computation and Storage in the Cloud is the first comprehensive and systematic work investigating the issue of computation and storage trade-off in the cloud in order to reduce the overall application cost. Scientific applications are usually computation and data intensive, where complex computation tasks take a long time for execution and the generated datasets are often terabytes or petabytes in size. Storing valuable generated application datasets can save their regeneration cost when they are reused, not to mention the waiting time caused by regeneration. However, the large size of the scientific datasets is a big challenge for their storage. By proposing innovative concepts, theorems and algorithms, this book will help bring the cost down dramatically for both cloud users and service providers to run computation and data intensive scientific applications in the cloud. Covers cost models and benchmarking that explain the necessary tradeoffs for both cloud providers and users Describes several novel strategies for storing application datasets in the cloud Includes real-world case studies of scientific research applications

Heterogeneous Computing with OpenCL

  • 2nd Edition
  • November 13, 2012
  • Benedict Gaster + 4 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 4 0 5 8 9 4 - 1
  • eBook
    9 7 8 - 0 - 1 2 - 4 0 5 5 2 0 - 9
Heterogeneous Computing with OpenCL, Second Edition teaches OpenCL and parallel programming for complex systems that may include a variety of device architectures: multi-core CPUs, GPUs, and fully-integrated Accelerated Processing Units (APUs) such as AMD Fusion technology. It is the first textbook that presents OpenCL programming appropriate for the classroom and is intended to support a parallel programming course. Students will come away from this text with hands-on experience and significant knowledge of the syntax and use of OpenCL to address a range of fundamental parallel algorithms. Designed to work on multiple platforms and with wide industry support, OpenCL will help you more effectively program for a heterogeneous future. Written by leaders in the parallel computing and OpenCL communities, Heterogeneous Computing with OpenCL explores memory spaces, optimization techniques, graphics interoperability, extensions, and debugging and profiling. It includes detailed examples throughout, plus additional online exercises and other supporting materials that can be downloaded at http://www.heterogeneouscompute.org/?page_id=7 This book will appeal to software engineers, programmers, hardware engineers, and students/advanced students.

CUDA Programming

  • 1st Edition
  • November 13, 2012
  • Shane Cook
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 4 1 5 9 3 3 - 4
  • eBook
    9 7 8 - 0 - 1 2 - 4 1 5 9 8 8 - 4
If you need to learn CUDA but don't have experience with parallel computing, CUDA Programming: A Developer's Introduction offers a detailed guide to CUDA with a grounding in parallel fundamentals. It starts by introducing CUDA and bringing you up to speed on GPU parallelism and hardware, then delving into CUDA installation. Chapters on core concepts including threads, blocks, grids, and memory focus on both parallel and CUDA-specific issues. Later, the book demonstrates CUDA in practice for optimizing applications, adjusting to new hardware, and solving common problems.

The Art of Multiprocessor Programming, Revised Reprint

  • 1st Edition
  • June 25, 2012
  • Maurice Herlihy + 1 more
  • English
  • eBook
    9 7 8 - 0 - 1 2 - 3 9 7 7 9 5 - 3
Revised and updated with improvements conceived in parallel programming courses, The Art of Multiprocessor Programming is an authoritative guide to multicore programming. It introduces a higher level set of software development skills than that needed for efficient single-core programming. This book provides comprehensive coverage of the new principles, algorithms, and tools necessary for effective multiprocessor programming. Students and professionals alike will benefit from thorough coverage of key multiprocessor programming issues.