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Parallel Computing: more books (100)

Introduction to Parallel Computing (2nd Edition) by Ananth Grama, George Karypis, et all 2003-01-26
Parallel Computing: Theory and Practice by Michael J. Quinn, 1993-09-01
High Performance Computing and the Art of Parallel Programming: An Introduction for Geographers, Social Scientists and Engineers by Stan Openshaw, Ian Turton, 2000-01-03
Communication Complexity and Parallel Computing (Texts in Theoretical Computer Science. An EATCS Series) by Juraj Hromkovic, 2010-11-02
Scientific Parallel Computing by L. Ridgway Scott, Terry Clark, et all 2005-03-28
Parallel Programming: for Multicore and Cluster Systems by Thomas Rauber, Gudula Rünger, 2010-03-10
Parallel Scientific Computing in C++ and MPI: A Seamless Approach to Parallel Algorithms and their Implementation by George Em Karniadakis, Robert M. Kirby II, 2003-06-16
Professional Parallel Programming with C#: Master Parallel Extensions with .NET 4 by Gaston Hillar, 2011-01-18
Introduction to Parallel Computing: Design and Analysis of Parallel Algorithms by Vipin Kumar, Ananth Grama, et all 1994-01
Parallel Computing: Numerics, Applications, and Trends
Parallel Programming: Techniques and Applications Using Networked Workstations and Parallel Computers (2nd Edition) by Barry Wilkinson, Michael Allen, 2004-03-14
The Sourcebook of Parallel Computing (The Morgan Kaufmann Series in Computer Architecture and Design)
Principles of Parallel Programming by Calvin Lin, Larry Snyder, 2008-03-07
Parallel MATLAB for Multicore and Multinode Computers (Software, Environments and Tools) by Jeremy Kepner, 2009-06-18

lists with details

Parallel Computing - Wikipedia, The Free Encyclopedia
Parallel computing is a form of computation in which many calculations are carried out simultaneously, operating on the principle that large problems can
http://en.wikipedia.org/wiki/Parallel_computing

Extractions: From Wikipedia, the free encyclopedia Jump to: navigation search Programming paradigms Language-oriented Non-structured (contrast: Structured Nondeterministic Parallel computing Programming in the large and programming in the small Structured (contrast: Non-structured Value-level (contrast: Function-level This box: view talk edit Parallel computing is a form of computation in which many calculations are carried out simultaneously, operating on the principle that large problems can often be divided into smaller ones, which are then solved concurrently ("in parallel"). There are several different forms of parallel computing: bit-level instruction level data , and task parallelism . Parallelism has been employed for many years, mainly in
Parallel Computing
Parallel computing. Parallel computing is the simultaneous execution of the same task (split up and specially adapted) on multiple processors in order to obtain faster results.
http://www.fact-index.com/p/pa/parallel_computing.html

Extractions: Main Page See live article Alphabetical index Parallel computing is the simultaneous execution of the same task (split up and specially adapted) on multiple processors in order to obtain faster results. The term parallel processor is sometimes used for a computer with more than one central processing unit , available for parallel processing. Systems with thousands of such processors are known as massively parallel There are many different kinds of parallel computer (or "parallel processor"). They are distinguished by the kind of interconnection between processors (known as "processing elements" or PEs) and between processors and memory. Flynn's taxonomy also classifies parallel (and serial) computers according to whether all processors execute the same instructions at the same time ( single instruction/multiple data SIMD ) or each processor executes different instructions ( multiple instruction/multiple data MIMD While a system of n parallel processors is not more efficient than one processor of n times the speed, the parallel system is often cheaper to build. Therefore, for tasks which require very large amounts of computation and/or have time constraints on completion, parallel computation is an excellent solution. In fact, in recent years, most high performance computing systems, also known as supercomputers, have a parallel architecture.
Parallel Computing - Simple English Wikipedia, The Free Encyclopedia
Parallel computing is a form of computation in which many instructions are carried out simultaneously (termed in parallel ), depending on the theory that large problems can often be
http://simple.wikipedia.org/wiki/Parallel_computing

Extractions: From Wikipedia, the free encyclopedia Jump to: navigation search Parallel computing is a form of computation in which many instructions are carried out simultaneously (termed "in parallel"), depending on the theory that large problems can often be divided into smaller ones, and then solved concurrently ("in parallel"). There are several different forms of parallel computing: Bit-level parallelism Instruction-level parallelism Data parallelism Task parallelism It has been used for many years, mainly in high-performance computing , with a great increase in its use in recent years, due to the physical constraints preventing frequency scaling . Parallel computing has become the main model in computer architecture , mainly in the form of multicore processors However, in recent years, power consumption by parallel computers has become a concern. Parallel computers can be classified according to the level at which the hardware supports parallelism—with multi-core and multi-processor computers having multiple processing elements inside a single machine, while
Parallel Computing -- CFD-Wiki, The Free CFD Reference
Introduction . Ever heard of Divide and Conquer ? Ever heard of Together we stand, divided we fall ? This is the whole idea of parallel computing.
http://www.cfd-online.com/Wiki/Parallel_computing

Extractions: Ever heard of "Divide and Conquer"? Ever heard of "Together we stand, divided we fall"? This is the whole idea of parallel computing. A complicated CFD problem involving combustion, heat transfer, turbulence, and a complex geometry needs to be tackled. The way to tackle it is to divide it and then conquer it. The computers unite their efforts to stand up to the challenge! Parallel computing is defined as the simultaneous use of more than one processor to execute a program. This formal definition holds a lot of intricacies inside. For instance, given a program, one cannot expect to run this program on a 1000 processors without any change to the original code. The program has to have instructions to guide it to run in parallel. Since the work is shared or distributed amongst "different" processors, data has to be exchanged now and then. This data exchange takes place using different methods depending on the type of parallel computer used. For example, using a network of PCs, a certain protocol has to be defined (or installed) to allow the data flow between PCs. The sections below describe some of the details involved. There are two fundamental types of parallel computers A single computer with multiple internal processors, known as a
Parallel Computing: Facts, Discussion Forum, And Encyclopedia Article
Computing, also known as computer science, is usually defined as the activity of using and improving computer technology, computer hardware and software.
http://www.absoluteastronomy.com/topics/Parallel_computing

Extractions: Home Discussion Topics Dictionary ... Login Parallel computing Discussion Ask a question about ' Parallel computing Start a new discussion about ' Parallel computing Answer questions from other users Full Discussion Forum Encyclopedia Parallel computing is a form of computation Computing Computing, also known as computer science, is usually defined as the activity of using and improving computer technology, computer hardware and software. It is the computer-specific part of information technology... in which many calculations are carried out simultaneously, operating on the principle that large problems can often be divided into smaller ones, which are then solved concurrently Concurrency (computer science) In computer science, concurrency is a property of systems in which several computations are executing simultaneously, and potentially interacting with each other... ("in parallel"). There are several different forms of parallel computing: bit-level Bit-level parallelism Bit-level parallelism is a form of parallel computing based on increasing processor word size. From the advent of very-large-scale integration computer chip fabrication technology in the 1970s until about 1986, advancements in computer architecture were done by increasing bit-level...
Parallel Computing
Q Any example of parallel computing in personal computers? Can anyone give me an example where parallel computing (to be more precise pipelining) is used in personal
http://www.kosmix.com/topic/Parallel_computing
Parallel Computing
File Format Microsoft Powerpoint View as HTML
http://www.cs.ucf.edu/courses/cot4810/fall04/presentations/Parallel_Computing.pp

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Parallel Computing - Definition
Parallel computing is the simultaneous execution of the same task (split up and specially adapted) on multiple processors in order to obtain faster results.
http://www.wordiq.com/definition/Parallel_computing

Extractions: 6 External links: The term parallel processor is sometimes used for a computer with more than one central processing unit , available for parallel processing. Systems with thousands of such processors are known as massively parallel There are many different kinds of parallel computers (or "parallel processors"). They are distinguished by the kind of interconnection between processors (known as "processing elements" or PEs) and between processors and memories. Flynn's taxonomy also classifies parallel (and serial) computers according to whether all processors execute the same instructions at the same time ( single instruction/multiple data SIMD ) or each processor executes different instructions ( multiple instruction/multiple data MIMD ). Parallel processor machines are also divided into symmetric and asymmetric multiprocessors, depending on whetever all the processors are capable of running all the operating system code and say acessing I/O devices or if some processors are more or less priviledged.
Introduction To Parallel Computing And Cluster Computers
This is a very basic introduction to the world of parallel computing. I ve tried to provide all the information needed to get started.
http://www.scl.ameslab.gov/Projects/parallel_computing/

Extractions: This is a very basic introduction to the world of parallel computing. I've tried to provide all the information needed to get started. There are also links to more additional information on more advanced topics. The last part is a basic introduction to designing and building cluster computers. Links to more advanced topics MP_Lite message-passing library documentation
Supercomputing And Parallel Computing Research Groups
Academic research groups and projects related to parallel computing.
http://www.cs.cmu.edu/~scandal/research-groups.html

Extractions: Supercomputing and Parallel Computing Research Groups Index Conferences Vendors Supercomputers Note: I've moved on to another job , and I can no longer afford the time to keep this site updated. I recommend IEEE's ParaScope as a good alternative. Academic research groups working in the field of supercomputing and parallel computing. High performance simulations of lattice gauge theories and QCD.
Parallel Computing Developer Center
Parallel Programming with Microsoft .NET Design Patterns for Decomposition and Coordination on Multicore Architectures This book describes patterns for parallel programming
http://msdn.microsoft.com/en-us/concurrency/default.aspx
Parallel Computing Toolbox - MATLAB
Parallel Computing Toolbox enables you to harness a multicore computer, GPU, cluster, grid, or cloud to solve computationally and dataintensive problems. The toolbox provides
http://www.mathworks.com/products/parallel-computing/

Extractions: var host_pre = "http://www"; Home Select Country Contact Us Store Search Create Account Log In Solutions Academia ... Installation Instructions Other Parallel Computing Resources Technical Literature User Stories Parallel Computing Toolbox™ lets you solve computationally and data-intensive problems using multicore processors, GPUs, and computer clusters. High-level constructs—parallel for-loops, special array types, and parallelized numerical algorithms—let you parallelize MATLAB applications without CUDA or MPI programming. You can use the toolbox with Simulink to run multiple simulations of a model in parallel. MATLAB GPU Support The toolbox provides eight workers (MATLAB computational engines) to execute applications locally on a multicore desktop. Without changing the code, you can run the same application on a computer cluster or a grid computing service (using MATLAB Distributed Computing Server ™). You can run parallel applications interactively or in batch. Parallel Computing with MATLAB on Amazon Elastic Compute Cloud (EC2)
Parallel Computing Works
A book about parallel computing, focusing on a few specific research projects done at Caltech.
http://www.netlib.org/utk/lsi/pcwLSI/text/

Extractions: Next: Contents This book describes work done at the Caltech Concurrent Computation Program , Pasadena, Califonia. This project ended in 1990 but the work has been updated in key areas until early 1994. The book also contains links to some current projects. Geoffrey C. Fox Roy D. Williams Paul C. Messina ISBN 1-55860-253-4 Morgan Kaufmann Publishers , Inc. 1994 ordering information We briefly describe the contents of this book The heart of this work is a set of applications largely developed at Caltech from 1985-1990 by the Caltech Concurrent Computation Group. These are linked to a set of tables and Glossaries Applications are classified into 5 problem classes: Such applications tend to be regular and characterised by algorithms employing simultaneous identical updates to a set of points, more in
ScienceDirect - Parallel Computing, Volume 36, Issue 12, Pages 645-712 (December
The online version of Parallel Computing on ScienceDirect, the world s leading platform for high quality peerreviewed full-text publications in science,
http://www.sciencedirect.com/science/journal/01678191

Extractions: Sample Issue Online About this Journal Submit your Article Shortcut link to this Title ... New Article Feed Signed up for new Volumes / Issues [ remove Alert me about new Volumes / Issues Your selection(s) could not be saved due to an internal error. Please try again. Added to Favorites [ remove Add to Favorites Font Size: Add to my Quick Links Volume 36, Issue 12, Pages 645-712 (December 2010) = Full-text available = Abstract only Articles in Press Volume 36 (2010) Volume 36, Issue 12 - selected
Nan's Parallel Computing Page
Links to online books, tutorials, and research projects.
http://www.cs.rit.edu/~ncs/parallel.html

Extractions: This list contains links related to parallel computing. If you have any suggestions please send me e-mail: Please note that an ' XXX ' at the end of a line means that I have recently (see the date at bottom of page) had trouble getting there. I am working on fixing/deleting these links. Nan Schaller's Interests Page e-mail: Nan Schaller's Home Page RIT's Home Page Parallel Computers Odyssey FAQ The sC++ language - Synchronous Java Applied Parallel Research, Inc. ARCH Library ... Tools for CSP MOSIX - Scalable Cluster Computing for Linux (Hebrew Univ.) Appleseed-parallel Macintosh Cluster IEEE CS Task Force on Cluster Computing Kal�ka, Distributed system for high performance parallel computing (Univ. of Auckland, NZ) SCL Cluster Cookbook Concordia Home Page Concurrent Programming Using the Java Language concurrency: State Models and Java Programs Infosphere Infrastructure - Current Release ... CTJ - Communicating Threads in Java (NL) Java(tm) Distributed Computing Java Parallel JavaOne Session Presentations TOPIC Links and Pages ... http://wwwipd.ira.uka.de/JavaParty/
Internet Parallel Computing Archive
Links to information about parallel algorithms, computing environments and tools, newsgroups, and general references.
http://wotug.ukc.ac.uk/parallel/
CRAN Task View: High-Performance And Parallel Computing With R
This CRAN task view contains a list of packages, grouped by topic, that are useful for highperformance computing (HPC) with R. In this context, we are defining 'high
http://cran.r-project.org/web/views/HighPerformanceComputing.html

Extractions: Maintainer: Dirk Eddelbuettel Contact: Version: This CRAN task view contains a list of packages, grouped by topic, that are useful for high-performance computing (HPC) with R. In this context, we are defining 'high-performance computing' rather loosely as just about anything related to pushing R a littler further: using compiled code, parallel computing (in both explicit and implicit modes), working with large objects as well as profiling. Unless otherwise mentioned, all packages presented with hyperlinks are available from CRAN, the Comprehensive R Archive Network. Several of the areas discussed in this Task View are undergoing rapid change. Please send suggestions for additions and extensions for this task view to the task view maintainer Suggestions and corrections by Achim Zeileis, Markus Schmidberger, Martin Morgan, Max Kuhn, Tomas Radivoyevitch, Jochen Knaus, Tobias Verbeke, Hao Yu, David Rosenberg, Marco Enea, Ivo Welch and Jay Emerson are gratefully acknowledged. Parallel computing: Explicit parallelism Several packages provide the communications layer required for parallel computing. The first package in this area was
Parallel Computing
Nov 5, 2008 Parallel computing simply means using more than one computer processor to solve a problem. Classically, computers have been presented to
http://cnx.org/content/m18099/latest/

Extractions: var portal_url="http://cnx.org"; Skip to content Skip to navigation Search: You are here: Home Content » Parallel Computing What is a lens? Lenses A lens is a custom view of the content in the repository. You can think of it as a fancy kind of list that will let you see content through the eyes of organizations and people you trust. What is in a lens? Lens makers point to materials (modules and collections), creating a guide that includes their own comments and descriptive tags about the content. Who can create a lens? Any individual member, a community, or a respected organization. What are tags? Tags are descriptors added by lens makers to help label content, attaching a vocabulary that is meaningful in the context of the lens. This content has been endorsed by the organizations listed. Click each link for a list of all content endorsed by the organization. This module is included in Lens: High Performance Computing Open Education Cup 2008-2009
IS PARALLEL COMPUTING DEAD?
Article about the future of the parallel computing industry.
http://www.crpc.rice.edu/newsletters/oct94/director.html

Extractions: Ken Kennedy, Director, CRPC Is parallel computing really dead? At the very least, it is undergoing a major transition. With the end of the cold war, there is less funding for defense-oriented supercomputing, which has been the traditional mainstay of the high-end market. If parallel computing is to survive in the new environment, a much larger fraction of sales must be to industry, which seems to be substantially less concerned with high-end performance. Two factors bear on the size of the industrial market for parallel computing. First, most engineering firms have recently made the transition away from mainframes to workstations. These companies believe that if they need more computational power than they have on a single workstation, they should be able to get it by using a network of such machines. Whether or not this is true, it has substantially affected sales of tightly coupled parallel systems and must be taken into account when analyzing the needs of industry users. A second factor affecting commercial sales of parallel computer systems has been the reluctance of independent software vendors like MacNeal- Schwendler to move their applications to parallel machines. I believe the primary reason for this reluctance has been the absence of an industry standard interface that supports machine-independent parallel programming. Without such a standard, a software vendor's investment in conversion to parallel machines is not protectedwhen a new parallel computing architecture with a new programming interface emerges, the application would need to be retargeted.
Introduction To Parallel Computing
Implicit Parallelism Trends in Microprocessor Architectures; Limitations of Memory System Performance; Dichotomy of Parallel Computing Platforms
http://www-users.cs.umn.edu/~karypis/parbook/

Extractions: Ananth Grama, Purdue University, W. Lafayette, IN 47906 (ayg@cs.purdue.edu Anshul Gupta, IBM T.J. Watson Research Center, Yorktown Heights, NY 10598 (anshul@watson.ibm.com George Karypis, University of Minnesota, Minneapolis, MN 55455 (karypis@cs.umn.edu Vipin Kumar, University of Minnesota, Minneapolis, MN 55455 (kumar@cs.umn.edu Follow this link for a recent review of the book published at IEEE Distributed Systems Online. The solutions are password protected and are only available to lecturers at academic institutions. Click here to apply for a password. Click here to download the solutions (PDF File). 1. Introduction (figures: [ PDF PS 2. Parallel Programming Platforms (figures: [ PPT PDF PS

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