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         Parallel Computing Programming:     more books (100)
  1. Parallel and Distributed Simulation Systems (Wiley Series on Parallel and Distributed Computing) by Richard M. Fujimoto, 2000-01-03
  2. Parallel Computing: Fundamentals, Applications and New Directions (Advances in Parallel Computing)
  3. Highly Parallel Computing (The Benjamin/Cummings Series in Computer Science and Engineering) by George S. Almasi, Allan Gottlieb, 1993-10
  4. Industrial Strength Parallel Computing
  5. Languages and Compilers for Parallel Computing: 15th Workshop, LCPC 2002, College Park, MD, USA, July 25-27, 2002, Revised Papers (Lecture Notes in Computer Science)
  6. Languages and Compilers for Parallel Computing: 7th International Workshop, Ithaca, NY, USA, August 8 - 10, 1994. Proceedings (Lecture Notes in Computer Science)
  7. Languages and Compilers for Parallel Computing: 12th International Workshop, LCPC'99 La Jolla, CA, USA, August 4-6, 1999 Proceedings (Lecture Notes in Computer Science)
  8. Languages and Compilers for Parallel Computing: 16th International Workshop, LCPC 2003, College Sation, TX, USA, October 2-4, 2003, Revised Papers (Lecture Notes in Computer Science)
  9. Languages and Compilers for Parallel Computing: Fourth International Workshop, Santa Clara, California, Usa, August 7-9M 1991, Proceedings (Lecture Notes in Computer Science) by U. Banarjee, David Gelernter, et all 1992-04
  10. Parallel Computing: From Theory to Sound Practice, (Transputer & Occam Engineering.) by Elie Milgrom, Spain) European Workshops on Parallel Computing (1992 Barcelona, 1992-01-01
  11. Neural Network Parallel Computing (The International Series in Engineering and Computer Science) by Yoshiyasu Takefuji, 1992-01-31
  12. Practical Applications of Parallel Computing: Advances in Computation: Theory and Practice (Advances in the Theory of Computational Mathematics, V. 12.)
  13. Languages for Parallel Architectures: Design, Semantics, Implementation Models (Wiley Series in Parallel Computing)
  14. Parallel Computing and Mathematical Optimization: Proceedings of the Workshop on Parallel Algorithms and Transputers for Optimization, Held at the UN (Lecture ... Notes in Economics and Mathematical Systems) by Workshop on Parallel Algorithms and Transputers for Optimization, Manfred Grauer, 1991-11

61. Uni Stuttgart - Faculty Of Computer Science
Faculty of Computer Science. Computer architecture, computing software, dialogue systems, formal concepts of computer science, graphical engineering systems, intelligent systems, programming languages, software engineering, theoretical computer science, parallel and distributed systems, image understanding, integrated systems engineering and large system simulation.
Home Organisation News Studies ... Who? What? Where? University of Stuttgart Faculties Faculty of Computer Science
In General
News Facilities Persons and Contacts Research Teaching and Studies Information Services Informatik-Forum Stuttgart e.V. (infos) Last update: 26. January 1999 ( wm

62. SAL- Parallel Computing - Programming Languages & Systems
Most parallel programming languages are conventional or sequential programming NESL a parallel programming language which is easy and portable.
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Most parallel programming languages are conventional or sequential programming languages with some parallel extensions. A compiler is a program that converts the source code written in a specific language into another format, eventually in assembly or machine code that a computer understands. For message-passing based distributed memory systems, "compilers" often map communication functions into prebuilt routines in communication libraries. Some systems listed here are basically communication libraries. However, they have their own integrated utilities and programming environments. Search SAL: Commercial, Shareware, GPL aCe a data-parallel computing environment designed to improve the adaptability of algorithms.
a High Performance Fortran compilation system.
an object-oriented programming system for distributed applications.
machine independent parallel programming system.
an algorithmic multithreaded language.
a higher order, pure and lazy functional programming language.

63. SAL- Parallel Computing - Programming Languages & Systems - ZPL
to run programs in parallel; otherwise, they are simply run as sequentialprograms. SAL Home parallel computing programming Languages Systems
ZPL ZPL is a new array programming language designed from first principles for fast execution on both sequential and parallel computers. Because ZPL benefits from recent research in parallel compilation, it provides a convenient high level programming medium for supercomputers with efficiency comparable to handcoded message passing. Users with scientific computing experience can generally learn ZPL in a few hours. Those who have used MATLAB or Fortran 90 may already be acquainted with the array programming style. Current Version: License Type: Free for Non-Commercial Use Home Site: Source Code Availability: No Available Binary Packages:
  • Debian Package: No
  • RedHat RPM Package: No
  • Other Packages: Yes
Targeted Platforms:
x86/Linux, Alpha/OSF, MIPS/IRIX, PowerPC/AIX, SPARC/Solaris, SGI Origin, SGI Power Challenge, Intel Paragon, IBM SP2, Cray T3D/T3E; contact authors for others. Software/Hardware Requirements:
C compiler, MPI or PVM is required to run programs in parallel; otherwise, they are simply run as sequential programs. Other Links:
None Mailing Lists/USENET News Groups:

64. Parallel Computing Toolkit For Mathematica: Inexpensive Computing Solution With
parallel computing Toolkit supports all common parallel programming paradigmssuch as parallel computing Toolkit implements many parallel programming
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Parallel Computing Toolkit Provides Inexpensive Computing Solution with High Functionality
February 7, 2000With the release of Parallel Computing Toolkit , Wolfram Research officially introduces parallel computing support for Mathematica Parallel Computing Toolkit for Mathematica makes parallel programming easily affordable to users with access to either a multiprocessor machine or a network of heterogeneous machineswithout requiring dedicated parallel hardware. Parallel Computing Toolkit can take advantage of existing Mathematica kernels on all supported operating systemsincluding Unix, Linux, Windows, and Macintoshconnected through TCP/IP, thus enabling users to use existing hardware and Mathematica licenses to create low-cost "virtual parallel computers."

65. DEVSEEK: Parallel Computing : Programming : Environments
Devseek The Programmer s Search Engine. Find useful web sites to help you inprogramming.
: Parallel Computing : Programming : Environments
  • Converse 4.8 - Converse is a component based portable run-time system, that allows easy implementation of run-time systems of novel parallel languages. It provides support for user-level threads, communication, shared memory and a collection of useful run-time libraries. (Added: 19-Jan-1999 )
  • Eiffel Parallel Execution Environment - EPEE is an object oriented design framework for programming distributed memory parallel computers. (Added: 19-Jan-1999 )
  • Harness Project - builds on the concept of the Distributed Virtual Machine that was pioneered by our PVM research, but fundamentally recreates this idea and explores dynamic capabilities beyond what PVM can supply. (Added: 19-Jan-1999 )
  • - Parallel programming system (Added: 19-Jan-1999 )
  • PAWS - Parallel Aplication Work Space - The goal of the PAWS project is to create a parallel, scientific, problem-solving environment: an integrated collection of software tools that scientists can use to facilitate solving problems.

66. DEVSEEK: Parallel Computing : Programming : Languages
Devseek The Programmer s Search Engine. Find useful web sites to help you inprogramming.
: Parallel Computing : Programming : Languages
  • Charm++ - A parallel extension to C++ developed at the Parallel Programming Laboratory for the past several years. Charm++ is a data driven (actor like) language. (Added: 19-Jan-1999 )
  • Jade - parallel language for distributed memory machines using SAM - Jade is a parallel programming language (an extension to C) for exploiting coarse-grain concurrency in sequential, imperative programs. Jade provides the convenience of a shared memory model by allowing any task to access shared objects transparently. (Added: 19-Jan-1999 )
  • mpC - Parallel Programming Environment - mpC is a high-level parallel language (an extention of ANSI C), designed specially to develop portable adaptable application for heterogeneous networks of computers. (Added: 19-Jan-1999 )
  • pC++/Sage++ Information - pC++ is a portable parallel C++ for high performance computers. pC++ is a language extention to C++ that permits data-parallel style opertations using "collections of objects" from some base "element" class. Sage++ is an object-oriented compiler preprocessor toolkit.

67. Parallel Computing Resources
Resources in parallel computing, maintained by Quentin Stout. MPI, the mostimportant standard for messagepassing programming.
Resources for Parallel Computing
This list is maintained at where the entries are linked to the resource. Rather than creating a comprehensive, overwhelming, list of resources, I have tried to be selective, pointing to the best ones that I am aware of in each category. You can send me an email to suggest modifications - I'm at qstout umich edu
  • A slightly whimsical explanation of parallel computing.
  • Tutorials
    • From Edinburgh Parallel Computing Center (EPCC): On-line courses include MPI, HPF, Mesh Generation, Introduction to Computational Science, HPC in Business.
    • From NCSA: On-line courses include MPI, OpenMP, and multilevel parallel programming (MPI + OpenMP).
    • Parallel Computing 101 , a tutorial for beginning and intermediate users, managers, people contemplating purchasing or building a parallel computer, etc.
  • Distributed Systems Online , a thorough and up-to-date listing of parallel and supercomputing sites, books, and events, maintained by the IEEE Computer Society.
  • Newsgroups: comp.parallel, comp.sys.super (there are many others on more specialized topics)

68. Paralell Computing
Internet parallel computing Archive Links to information about parallel Reading List on parallel programming Languages at Case Western U.

" A scientific truth does not triumph by convincing its opponents and making them see the light, but rather because its opponents eventually die and a new generation grows up that is familiar with it ." - Maxwell Planck
Algorithms Compilers Computational Geometry Computer Architecture ... Operating Systems
Parallel and Distributed Algorithms
Parallel Computing Links

69. Manning: Distributed And Parallel Computing
Distributed and parallel computing is a comprehensive survey of the programming languages and systems for writing parallel and distributed programs
Home Ordering Info Shopping Cart Manage My Account ... Distributed and Parallel Computing
Inside the book
Sample Chapters Table of Contents Index Introduction ... Book Reviews
Manning Blog
Why small is sweet?
Author Blogs
Eric Pascarello more...
Author Calendar
Java .NET Perl XML ... All by Title
Manning Contact Us FAQs ebooks ... Jobs Manning Publications Co. 209 Bruce Park Avenue Greenwich, CT 06830 Distributed and Parallel Computing Hesham El-Rewini and Ted G. Lewis ISBN: 1884777511 Hardbound print book: $60.00 Currently Out of Stock Send email to for more information.
Distributed and Parallel Computing is a comprehensive survey of the state-of-the-art in concurrent computing. It covers four major aspects:
  • Architecture and performance
  • Theory and complexity analysis of parallel algorithms
  • Programming languages and systems for writing parallel and distributed programs
  • Scheduling of parallel and distributed tasks
Cutting across these broad topical areas are the various "programming paradigms", e.g., data parallel, control parallel, and distributed programming. After developing these fundamental concepts, the authors illustrate them in a wide variety of algorithms and programming languages. Of particular interest is the final chapter which shows how Java can be used to write distributed and parallel programs. This approach gives the reader a broad, yet insightful, view of the field. Many books on parallel computing have been published during the last 10 years or so. Most are already outdated since the themes and technologies in this area are changing very rapidly. Particularly, the notion that parallel and distributed computing are two separate fields is now beginning to fade away; technological advances have been bridging the gap.

70. CFD Resources Online - Parallel Computers
parallel Info. Internet parallel computing Archive Distributing computing forAerosciences Applications Proceedings parallel programming in C++

71. ProQuest Information And Learning - Introduction To Parallel Computing, Second E
There is no other book as clear and concise as this one. If you need an introductionto parallel computing / programming, buy this book now!
ProQuest Information and Learning Company Home Desktop Bookshelf Notes ... Bookmarks
Introduction to Parallel Computing, Second Edition By Ananth Grama Anshul Gupta George Karypis Vipin Kumar Publisher: Addison Wesley Pub Date: January 16, 2003 ISBN: Pages: Slots:
Table of Contents
Increasingly, parallel processing is being seen as the only cost-effective method for the fast solution of computationally large and data-intensive problems. The emergence of inexpensive parallel computers such as commodity desktop multiprocessors and clusters of workstations or PCs has made such parallel methods generally applicable, as have software standards for portable parallel programming. This sets the stage for substantial growth in parallel software. Data-intensive applications such as transaction processing and information retrieval, data mining and analysis and multimedia services have provided a new challenge for the modern generation of parallel platforms. Emerging areas such as computational biology and nanotechnology have implications for algorithms and systems development, while changes in architectures, programming models and applications have implications for how parallel platforms are made available to users in the form of grid-based services. This book takes into account these new developments as well as covering the more traditional problems addressed by parallel computers.Where possible it employs an architecture-independent view of the underlying platforms and designs algorithms for an abstract model. Message Passing Interface (MPI), POSIX threads and OpenMP have been selected as programming models and the evolving application mix of parallel computing is reflected in various examples throughout the book.

72. BSP Worldwide Home Page
of the Bulk Synchronous parallel (BSP) computing model for parallel programming . Published in parallel computing 24 (1998) pp. 19471980.
BSP Worldwide is an association of people interested in the development of the Bulk Synchronous Parallel (BSP) computing model for parallel programming. It exists to provide a convenient means for the exchange of ideas and experiences about BSP and to stimulate the use of the BSP model. Areas of interest of BSP Worldwide include:
  • Research into properties of the model Application of the model to programming tasks of all kinds including the scheduling of parallel execution Performance benchmarking and comparison with other approaches Cost modelling and performance prediction Definition of standard functions for programming in the BSP style Implementation of programming tools to support the use of the model
The organisation does not have a formal structure. Its activities depend on contributions by volunteers, BSP users, and developers.
Current BSP Work
Have a look at the BSP in the third millenium page for details of current activities.
BSPlib standard and implementation
Standard: BSPlib: the BSP Programming Library , by Jonathan Hill, Bill McColl, Dan Stefanescu, Mark Goudreau, Kevin Lang, Satish Rao, Torsten Suel, Thanasis Tsantilas, and Rob Bisseling, version with C examples or with Fortran 77 examples . Published in Parallel Computing (1998) pp. 1947-1980.

73. The MpC Parallel Programming Language And Its Programming Environment For Comput
parallel computing on Heterogeneous Networks. RTSS manages processes,constituting the parallel program, and provides communications.
The mpC Parallel Programming Environment
mpC Workshop

an mpC Intergated Development Environment for Windows is released.
Have a look how it looks like.
A book about mpC
Download free mpC software

Tarred and gzipped C-source distributions:
  • mpC v2.3.0
  • mpC v2.2.0
    mpC installation requirements: Network of UNIX workstations/PCs running MPI (LAM or MPICH implementations).
    Version history
  • mpC Tutorial ( .html
  • mpC Language Specification ( .html gzipped postscript mpC Program Examples Other Projects of the mpC Team
  • The C[] Programming Language and Its Compiler The C[] language is Fortran90-like ANSI C extention supporting array-based computations. mpC team proposes cooperation to parallel application developers mpC Programming Language in Brief mpC is a high-level parallel language (an extension of ANSI C), designed specially to develop portable adaptable applications for heterogeneous networks of computers. The main idea underlying mpC is that an mpC application explicitly defines an abstract network and distributes data, computations and communications over the network. The mpC programming system uses this information to map the abstract network to any real executing network in such a way that ensures efficient running of the application on this real network. This mapping is performed in run time and based on information about performances of processors and links of the real network, dynamically adapting the program to the executing network.
  • 74. Distributed Parallel Computing Using Navigational Programming
    Distributed parallel computing using navigational programming Lei Pan, Universityof California, Irvine M K. Lai K Noguchi J J. Huseynov
    Distributed parallel computing using navigational programming
    Lei Pan,
    University of California, Irvine
    M K. Lai

    K Noguchi
    Download the Article
    (500 K, PDF file) - 2004 Tell a colleague about it. Printing Tips : Select 'print as image' in the Acrobat print dialog if you have trouble printing. ABSTRACT:
    Message Passing ( MP) and Distributed Shared Memory (DSM) are the two most common approaches to distributed parallel computing. MP is difficult to use, whereas DSM is not scalable. Performance scalability and ease of programming can be achieved at the same time by using navigational programming (NavP). This approach combines the advantages of MP and DSM, and it balances convenience and flexibility. Similar to MP, NavP suggests to its programmers the principle of pivot-computes and hence is efficient and scalable. Like DSM, NavP supports incremental parallelization and shared variable programming and is therefore easy to use. The implementation and performance analysis of real-world algorithms, namely parallel Jacobi iteration and parallel Cholesky factorization, presented in this paper supports the claim that the NavP approach is better suited for general-purpose parallel distributed programming than either MP or DSM. SUGGESTED CITATION:
    Lei Pan, M K. Lai, K Noguchi, J J. Huseynov, L F. Bic, and M B. Dillencourt, "Distributed parallel computing using navigational programming" (2004). International Journal of Parallel Programming. 32 (1), pp. 1-37. Postprint available free at:

    75. Computer Science - CS 415 Parallel Programming (4 Credits)
    An introduction to parallel programming concepts and techniques. parallelprogramming and learn programming skills on actual parallel computing systems.

    76. Lecture College Parallel Programmeren
    NB There is a separate Practical course parallel programming of 6 ECTS The class has a brief introduction into parallel computing systems
    Lecture Parallel Programming (2004)
    NOTE: The last lecture is on 6 December.
    NOTE: The exam has been moved to 21 January !
    NB: There is a separate Practical course Parallel Programming of 6 ECTS
    • You can start after the MPI lecture (18 October)
    • Register through email to (Rob van Nieuwpoort)
    • Deadline for submitting the assignments: 1 February 2004

    NB For information about the Scientific Visualization class see here. It starts 2 November 2004 at 11am in Room 1.11.
    Lecturer prof dr ir H.E. Bal Period Fall Credits 6 ECTS Time/location monday 11.00 - 13.00, zaal S111. Content This lecture discusses how programs can be written that run in parallel on a large number of processors, with the goal of reducing execution time. The class has a brief introduction into parallel computing systems (architectures). The focus of the class, however, is on programming methods, languages, and applications. Both traditional techniques (like message passing) and more advanced techniques (like parallel object-oriented languages and Tuple Space) will be discussed. In addition, attention is paid to implementation aspects of several languages. Finally, several parallel applications are discussed, including N-body simulations and game tree search. The class fits well with existing research projects within the department of Computing Systems. It is a good basis for M.Sc. projects in the area of parallel programming, which use the parallel computing systems of the department. Form

    77. Patterns For Parallel Programming - $34.99
    parallel programming Environments. The Jargon of parallel computing. A QuantitativeLook at parallel Computation. Communication. Summary.
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    78. Parallel Computing, Volume 24
    Special Double Issue Languages and Compilers for parallel Computers Special Issue Coordination Languages for parallel programming
    Parallel Computing , Volume 24
    Volume 24, Number 1, January 1998
    Special Issue on Applications: Parallel Data Servers and Applications
    Volume 24, Number 2, February 1998
    Practical Aspects

    79. SAL Parallel Computing
    parallel computing. programming Languages Systems Charm/Charm++, CODE, Erlang,HPF, uC++ Communication Libraries BSPlib, LinuxThreads, MPI, Para++,

    80. Introduction To Parallel Programming
    Overview, Up to Sequential programming Down to parallel computing? There aremany methods of programming parallel computers. Two of the most common are
    SP Parallel Programming Workshop p a r a l l e l p r o g r a m m i n g i n t r o d u c t i o n
    Table of Contents
  • Overview
  • What is Parallelism?
  • Sequential Programming
  • The Need for Faster Machines ...
  • References and More Information
    Overview What is Parallelism? A strategy for performing large, complex tasks faster. A large task can either be performed serially, one step following another, or can be decomposed into smaller tasks to be performed simultaneously, i.e., in parallel. Parallelism is done by:
    • Breaking up the task into smaller tasks
    • Assigning the smaller tasks to multiple workers to work on simultaneously
    • Coordinating the workers
    Parallel problem solving is common. Examples: building construction; operating a large organization; automobile manufacturing plant The automobile analogy.
    Overview Sequential Programming Traditionally, programs have been written for serial computers:
    • One instruction executed at a time
    • Using one processor
    • Processing speed dependent on how fast data can move through hardware
      • Speed of Light = 30 cm/nanosecond
      • Limits of Copper Wire = 9 cm/nanosecond
    • Fastest machines execute approximately 1 instruction in 9-12 billionths of a second

    Overview The Need for Faster Machines You might think that one instruction executed in 9 billionths of a second would be fast enough. You'd be wrong.
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