Designed for undergraduate/graduate-level parallel programming courses.
This nontheoretical, highly accessible text--which is linked to real parallel programming software--covers the
techniques of parallel programming in a practical manner that enables students to write and evaluate their parallel
programs. Supported by the National Science Foundation and exhaustively class-tested, it is the first text of its
kind that does not require access to a special multiprocessor system, concentrating instead only on parallel programs
that can be executed on networked workstations using freely available parallel software tools. The Second Edition
has been revised to incorporate a greater focus on cluster programming as this type of programming has become more
widespread with the availability of low-cost computers.
Features
NEW - Chapter on Distributed Shared Memory (DSM) programming--Describes techniques and tools for shared memory
programming on clusters.
Enables programs to be written in shared memory paradigm which has advantages over traditional message passing
programming.
NEW - Content revisions throughout.
Provides students with the most current and concise information possible.
NEW - Updated Companion Website--Includes revised step-by-step instructions for students and extensive support
materials for instructors such as PowerPoint slides and assignments.
Provides a resource that complements the text in a variety of ways that will help both students and professors
in and out of the classroom.
NEW - Required software (MPI, PVM, DSM) available FREE!
Students are provided with all the learning materials necessary for success in the course.
Usage of MPI and PVM pseudocodes.
Describes algorithms and allows different programming tools to be implemented.
Thorough coverage of shared memory programming and Pthreads.
Assists student in shared memory programming assignments.
Exploration of such applications as numerical algorithms, image processing and searching and optimization.
New To This Edition
Chapter on Distributed Shared Memory (DSM) programming--Describes techniques and tools for shared memory programming
on clusters.
Enables programs to be written in shared memory paradigm which has advantages over traditional message passing
programming.
Content revisions throughout.
Provides students with the most current and concise information possible.
Updated Companion Website--Includes revised step-by-step instructions for students and extensive support materials
for instructors such as PowerPoint slides and assignments.
Provides a resource that complements the text in a variety of ways that will help both students and professors
in and out of the classroom.
Required software (MPI, PVM, DSM) available FREE!
Students are provided with all the learning materials necessary for success in the course.
Table of Contents
I. BASIC TECHNIQUES.
1. Parallel Computers.
2. Message-Passing Computing.
3. Embarrassingly Parallel Computations.
4. Partitioning and Divide-and-Conquer Strategies.
5. Pipelined Computations.
6. Synchronous Computations.
7. Load Balancing and Termination Detection.
8. Programming with Shared Memory.
9. Distributed Shared Memory Systems and Programming.