9 edition of Parallel and distributed programming using C++ found in the catalog.
Published
2004
by Prentice Hall in Upper Saddle River, NJ
.
Written in English
Edition Notes
| Statement | Cameron and Tracey Hughes. |
| Contributions | Hughes, Tracey. |
| Classifications | |
|---|---|
| LC Classifications | QA76.642 .H83 2004 |
| The Physical Object | |
| Pagination | p. cm. |
| ID Numbers | |
| Open Library | OL3677154M |
| ISBN 10 | 0131013769 |
| LC Control Number | 2003016039 |
Parallel and Distributed Programming Using C++ provides an up-close look at how to build software that can take advantage of multiprocessor computers. Simple approaches for programming parallel virtual machines are presented, and 2/5(1). This book helps software developers and programmers who need to add the techniques of parallel and distributed programming to existing applications. Parallel programming uses multiple computers, or computers with multiple internal processors, to solve a problem at a greater computational speed than using a single computer.
Parallel programs for scientific computing on distributed memory clusters are most commonly written using the message passing interface (MPI) library. Programming with MPI is more difficult than programming with OpenNMP because of the difficulty of deciding how to distribute the work and how processes will communicate by message passing. Parallel Programming: Concepts and Practice provides an upper level introduction to parallel programming. In addition to covering general parallelism concepts, this text teaches practical programming skills for both shared memory and distributed memory architectures.
A C++ implementation of a periodic-pattern matching parallel algorithm using MPICH implementation of the MPI distributed-computing standard c distributed-systems hpc pattern-matching parallel mpi distributed-computing cpp11 mpi-applications openmpi mpich hpc-applications parallel-programming. The Benefits of Parallel Programming; The Benefits of Distributed Programming; The Minimal Effort Required; The Basic Layers of Software Concurrency; No Keyword Support for Parallelism in C++; Programming Environments for Parallel and Distributed Programming; Summary: Toward Concurrency. Chapter 2: The Challenges of Parallel and Distributed.
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Parallel and Distributed Programming Using C++ provides an architectural approach to parallel programming for computer programmers, software developers, designers, researchers, and software architects.
It will also be useful for computer science students. Demonstrates how agents and blackboards can be used to make parallel programming easierCited by: C++ has no keyword support for Parallel and distributed programming using C++ book. One must rely on libraries for parallel and distributed applications in C++.
This turns out to be a good thing because the C++ programmer isn't stuck with only one concurrency model supported by the language. Instead there are several standard options: POSIX (pthreads), MPI, PVM and CORBA/5(10).
Parallel and Distributed Programming Using C++. Provides an up-close look at how to build software that takes advantage of multiprocessor computers. Through an overview of multithreaded programming, this book shows you how to write software components that work together over a network to solve problems and do work.3/5(3).
Intended for programmers familiar with C++, this book explains how the C++ standard library, algorithms, and container classes behave in distributed and parallel environments, and offers methods for extending the C++ language through class libraries and function libraries to accomplish distributed and parallel programming tasks.
Parallel and Distributed Programming Using C++ August August Read More. Authors: Cameron Hughes, ; Tracy Hughes. By hiding the architecture-specific constructs required for high performance inside platform-independent abstractions, parallel object-oriented programming systems may be able to combine the speed of massively-parallel computing with the comfort of sequential programming.
Parallel Programming Using C++ describes fifteen parallel programming systems based on C++, the most popular object 5/5(1). The Parallel and Distributed Programming Using C++ is kind of book which is giving the reader capricious experience.
Parallel Programming Using C++ describes fifteen parallel programming systems based on C++, the most popular object-oriented language of today. These systems cover the whole spectrum of parallel programming paradigms, from data parallelism through dataflow and distributed shared memory to message-passing control parallelism.
For parallel programming in C++, we use a library, called PASL, that we have been developing over the past 5 years. The implementation of the library uses advanced scheduling techniques to run parallel programs efficiently on modern multicores and provides a range of utilities for understanding the behavior of parallel programs.
Parallel and Distributed Programming Using C++. Today, the C++ language remains one of the most important languages used by professional software developers. Many corporations and government agencies have large investments in applications that are developed using the C++ language/5(2).
Parallel and Distributed Programming Using C++ provides an architectural approach to parallel programming for computer programmers, software developers, designers, researchers, and software architects.
It will also be useful for computer science students.3/5(3). Parallel and Distributed Programming Using C++ provides an architectural approach to parallel programming for computer programmers, software developers, designers, researchers, and software architects.
It will also be useful for computer science students. Demonstrates how agents and blackboards can be used to make parallel programming easier. Parallel and Distributed Programming Using C++ provides an architectural approach to parallel programming for computer programmers, software developers, designers, researchers, and software architects.
It will also be useful for computer science students. Demonstrates how agents and blackboards can be used to make parallel programming easier3/5(3). The library approach to parallel and distributed programming gives the C++ programmer the greatest possible flexibility. While parallel and distributed programming can be fun and rewarding, it presents several challenges.
In the next chapter we will provide an overview of the most common challenges to parallel and distributed programming. Example Using the MessageId tag to distinguish data types. Example Using PVM to implement MPMD model of computation.
Programs. programcc Uses pvm_send to send a number to another PVM task that is executing. programcc Receives a number from its parent process and sends the result to its parent process.
Program Profiles. Program 6. Parallel and Distributed Programming Using C++ provides an architectural approach to parallel programming for computer programmers, software developers, designers, researchers, and software architects.
It will also be useful for computer science students. Demonstrates how agents and blackboards can be used to make parallel programming easier2/5(1). It is important to note that C++ container classes, stream classes, and template algorithms add flexibility to PVM programming that cannot be easily implemented in other PVM environments.
This flexibility creates opportunities for sophisticated yet elegant parallel architectures. Using the MPMD (MIMD) Model with PVM and C++. From the Publisher:Parallel and Distributed Programming Using C++ provides an up-close look at how to build software that can take advantage of multiprocessor computers.
Combining the C++ Runtime Library and the PVM Library Since access to the PVM is provided through a collection of library routines, a C++ program treats the PVM as any other library. Keep in mind that each PVM program is a standalone C++ program with its own main() function.
This means that each PVM program has its own address space. "Parallel Programming Using C++" describes fifteen parallel programming systems based on C++, the most popular object-oriented language of today.
These systems cover the whole spectrum of parallel programming paradigms, from data parallelism through dataflow and distributed shared memory to message-passing control parallelism.
One must rely on libraries for parallel and distributed applications in C++. This turns out to be a good thing because the C++ programmer isn't stuck with only one concurrency model supported by the language. Instead there are several standard options: POSIX (pthreads), MPI, PVM and CORBA/5.Description.
Parallel and Distributed Programming Using C++ provides an up-close look at how to build software that can take advantage of multiprocessor computers. Simple approaches for programming parallel virtual machines are presented, and .Get this from a library!
Parallel and distributed programming using C++. [Cameron Hughes; Tracey Hughes].
