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 the basics of cluster application development are explained. Through an easy-to-understand overview of multithreaded programming, this book also shows you how to write software components that work together over a network to solve problems and do work.

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.

We present an architectural approach to distributed and parallel programming using the C++ language. Particular attention is paid to how the C++ standard library, algorithms, and container classes behave in distributed and parallel environments. Methods for extending the C++ language through class libraries and function libraries to accomplish distributed and parallel programming tasks are explained. Emphasis is placed on how C++ works with the new POSIX and Single UNIX standards for multithreading. Combining C++ executables with other language executables to achieve multilingual solutions to distributed or parallel programming problems is also discussed. Several methods of organizing software that support parallel and distributed programming are introduced.

We demonstrate how to remove the fundamental obstacles to concurrency. The notion of emergent parallelization is explored. Our focus is not on optimization techniques, hardware specifics, performance comparisons, or on trying to apply parallel programming techniques to complex scientific or mathematical algorithms; rather, on how to structure computer programs and software systems to take advantage of opportunities for parallelization. Furthermore, we acquaint the reader with a multiparadigm approach to solving some of the problems that are inherent with distributed and parallel programming. Effective solutions to these problems often require a mix of several software design and engineering approaches. For instance, we deploy object-oriented programming techniques to tackle data race and synchronization problems. We use agent-oriented architectures to deal with multi-process and multithread management. Blackboards are used to minimize communication issues. In addition to object-oriented, agent-oriented, and AI-oriented programming, we use parameterized programming to implement generalized algorithms that are suitable where concurrency is required. Our experience with the development of software of all sizes and shapes has led us to believe that successful software design and implementation demands versatility. The suggestions, ideas, and solutions we present in this book reflect that experience.