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Highly Parallel Computing

Highly Parallel Computing PDF Author: George S. Almasi
Publisher: Addison Wesley Longman
ISBN:
Category : Computers
Languages : en
Pages : 726

Book Description
This second edition includes new exercises for each chapter, a quantitative treatment of speedup, seismic migration, using a workstation network as a parallel computer, recent changes in technology, more languages, fat trees, wormhole switching, new SIMD hardware, an expanded section on CM-2, new MIMD hardware, using workstation clusters as a MIMD system, and directory based caches. Annotation copyright by Book News, Inc., Portland, OR

Highly Parallel Computing

Highly Parallel Computing PDF Author: George S. Almasi
Publisher: Addison Wesley Longman
ISBN:
Category : Computers
Languages : en
Pages : 726

Book Description
This second edition includes new exercises for each chapter, a quantitative treatment of speedup, seismic migration, using a workstation network as a parallel computer, recent changes in technology, more languages, fat trees, wormhole switching, new SIMD hardware, an expanded section on CM-2, new MIMD hardware, using workstation clusters as a MIMD system, and directory based caches. Annotation copyright by Book News, Inc., Portland, OR

Programming Massively Parallel Processors

Programming Massively Parallel Processors PDF Author: David B. Kirk
Publisher: Newnes
ISBN: 0123914183
Category : Computers
Languages : en
Pages : 519

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

Parallel Computing Works!

Parallel Computing Works! PDF Author: Geoffrey C. Fox
Publisher: Elsevier
ISBN: 0080513514
Category : Computers
Languages : en
Pages : 1012

Book Description
A clear illustration of how parallel computers can be successfully appliedto large-scale scientific computations. This book demonstrates how avariety of applications in physics, biology, mathematics and other scienceswere implemented on real parallel computers to produce new scientificresults. It investigates issues of fine-grained parallelism relevant forfuture supercomputers with particular emphasis on hypercube architecture. The authors describe how they used an experimental approach to configuredifferent massively parallel machines, design and implement basic systemsoftware, and develop algorithms for frequently used mathematicalcomputations. They also devise performance models, measure the performancecharacteristics of several computers, and create a high-performancecomputing facility based exclusively on parallel computers. By addressingall issues involved in scientific problem solving, Parallel ComputingWorks! provides valuable insight into computational science for large-scaleparallel architectures. For those in the sciences, the findings reveal theusefulness of an important experimental tool. Anyone in supercomputing andrelated computational fields will gain a new perspective on the potentialcontributions of parallelism. Includes over 30 full-color illustrations.

Parallel and High Performance Computing

Parallel and High Performance Computing PDF Author: Robert Robey
Publisher: Simon and Schuster
ISBN: 1638350388
Category : Computers
Languages : en
Pages : 702

Book Description
Parallel and High Performance Computing offers techniques guaranteed to boost your code’s effectiveness. Summary Complex calculations, like training deep learning models or running large-scale simulations, can take an extremely long time. Efficient parallel programming can save hours—or even days—of computing time. Parallel and High Performance Computing shows you how to deliver faster run-times, greater scalability, and increased energy efficiency to your programs by mastering parallel techniques for multicore processor and GPU hardware. About the technology Write fast, powerful, energy efficient programs that scale to tackle huge volumes of data. Using parallel programming, your code spreads data processing tasks across multiple CPUs for radically better performance. With a little help, you can create software that maximizes both speed and efficiency. About the book Parallel and High Performance Computing offers techniques guaranteed to boost your code’s effectiveness. You’ll learn to evaluate hardware architectures and work with industry standard tools such as OpenMP and MPI. You’ll master the data structures and algorithms best suited for high performance computing and learn techniques that save energy on handheld devices. You’ll even run a massive tsunami simulation across a bank of GPUs. What's inside Planning a new parallel project Understanding differences in CPU and GPU architecture Addressing underperforming kernels and loops Managing applications with batch scheduling About the reader For experienced programmers proficient with a high-performance computing language like C, C++, or Fortran. About the author Robert Robey works at Los Alamos National Laboratory and has been active in the field of parallel computing for over 30 years. Yuliana Zamora is currently a PhD student and Siebel Scholar at the University of Chicago, and has lectured on programming modern hardware at numerous national conferences. Table of Contents PART 1 INTRODUCTION TO PARALLEL COMPUTING 1 Why parallel computing? 2 Planning for parallelization 3 Performance limits and profiling 4 Data design and performance models 5 Parallel algorithms and patterns PART 2 CPU: THE PARALLEL WORKHORSE 6 Vectorization: FLOPs for free 7 OpenMP that performs 8 MPI: The parallel backbone PART 3 GPUS: BUILT TO ACCELERATE 9 GPU architectures and concepts 10 GPU programming model 11 Directive-based GPU programming 12 GPU languages: Getting down to basics 13 GPU profiling and tools PART 4 HIGH PERFORMANCE COMPUTING ECOSYSTEMS 14 Affinity: Truce with the kernel 15 Batch schedulers: Bringing order to chaos 16 File operations for a parallel world 17 Tools and resources for better code

Using OpenCL

Using OpenCL PDF Author: Janusz Kowalik
Publisher: IOS Press
ISBN: 1614990298
Category : Computers
Languages : en
Pages : 312

Book Description


Programming Models for Parallel Computing

Programming Models for Parallel Computing PDF Author: Pavan Balaji
Publisher: MIT Press
ISBN: 0262528819
Category : Computers
Languages : en
Pages : 488

Book Description
An overview of the most prominent contemporary parallel processing programming models, written in a unique tutorial style. With the coming of the parallel computing era, computer scientists have turned their attention to designing programming models that are suited for high-performance parallel computing and supercomputing systems. Programming parallel systems is complicated by the fact that multiple processing units are simultaneously computing and moving data. This book offers an overview of some of the most prominent parallel programming models used in high-performance computing and supercomputing systems today. The chapters describe the programming models in a unique tutorial style rather than using the formal approach taken in the research literature. The aim is to cover a wide range of parallel programming models, enabling the reader to understand what each has to offer. The book begins with a description of the Message Passing Interface (MPI), the most common parallel programming model for distributed memory computing. It goes on to cover one-sided communication models, ranging from low-level runtime libraries (GASNet, OpenSHMEM) to high-level programming models (UPC, GA, Chapel); task-oriented programming models (Charm++, ADLB, Scioto, Swift, CnC) that allow users to describe their computation and data units as tasks so that the runtime system can manage computation and data movement as necessary; and parallel programming models intended for on-node parallelism in the context of multicore architecture or attached accelerators (OpenMP, Cilk Plus, TBB, CUDA, OpenCL). The book will be a valuable resource for graduate students, researchers, and any scientist who works with data sets and large computations. Contributors Timothy Armstrong, Michael G. Burke, Ralph Butler, Bradford L. Chamberlain, Sunita Chandrasekaran, Barbara Chapman, Jeff Daily, James Dinan, Deepak Eachempati, Ian T. Foster, William D. Gropp, Paul Hargrove, Wen-mei Hwu, Nikhil Jain, Laxmikant Kale, David Kirk, Kath Knobe, Ariram Krishnamoorthy, Jeffery A. Kuehn, Alexey Kukanov, Charles E. Leiserson, Jonathan Lifflander, Ewing Lusk, Tim Mattson, Bruce Palmer, Steven C. Pieper, Stephen W. Poole, Arch D. Robison, Frank Schlimbach, Rajeev Thakur, Abhinav Vishnu, Justin M. Wozniak, Michael Wilde, Kathy Yelick, Yili Zheng

High Performance Compilers for Parallel Computing

High Performance Compilers for Parallel Computing PDF Author: Michael Joseph Wolfe
Publisher: Addison Wesley
ISBN:
Category : Computers
Languages : en
Pages : 600

Book Description
Software -- Operating Systems.

Parallel Computer Architecture

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

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.

Handbook of Parallel Computing and Statistics

Handbook of Parallel Computing and Statistics PDF Author: Erricos John Kontoghiorghes
Publisher: CRC Press
ISBN: 9781420028683
Category : Computers
Languages : en
Pages : 560

Book Description
Technological improvements continue to push back the frontier of processor speed in modern computers. Unfortunately, the computational intensity demanded by modern research problems grows even faster. Parallel computing has emerged as the most successful bridge to this computational gap, and many popular solutions have emerged based on its concepts

Parallel I/O for High Performance Computing

Parallel I/O for High Performance Computing PDF Author: John M. May
Publisher: Morgan Kaufmann
ISBN: 9781558606647
Category : Computers
Languages : en
Pages : 392

Book Description
"I enjoyed reading this book immensely. The author was uncommonly careful in his explanations. I'd recommend this book to anyone writing scientific application codes." -Peter S. Pacheco, University of San Francisco "This text provides a useful overview of an area that is currently not addressed in any book. The presentation of parallel I/O issues across all levels of abstraction is this book's greatest strength." -Alan Sussman, University of Maryland Scientific and technical programmers can no longer afford to treat I/O as an afterthought. The speed, memory size, and disk capacity of parallel computers continue to grow rapidly, but the rate at which disk drives can read and write data is improving far less quickly. As a result, the performance of carefully tuned parallel programs can slow dramatically when they read or write files-and the problem is likely to get far worse. Parallel input and output techniques can help solve this problem by creating multiple data paths between memory and disks. However, simply adding disk drives to an I/O system without considering the overall software design will not significantly improve performance. To reap the full benefits of a parallel I/O system, application programmers must understand how parallel I/O systems work and where the performance pitfalls lie. Parallel I/O for High Performance Computing directly addresses this critical need by examining parallel I/O from the bottom up. This important new book is recommended to anyone writing scientific application codes as the best single source on I/O techniques and to computer scientists as a solid up-to-date introduction to parallel I/O research. Features: An overview of key I/O issues at all levels of abstraction-including hardware, through the OS and file systems, up to very high-level scientific libraries. Describes the important features of MPI-IO, netCDF, and HDF-5 and presents numerous examples illustrating how to use each of these I/O interfaces. Addresses the basic question of how to read and write data efficiently in HPC applications. An explanation of various layers of storage - and techniques for using disks (and sometimes tapes) effectively in HPC applications.