I chose the transputer because it offers good cost/performance trade-offs, making it attractive for small computer science or computer engineering departments, as well as for individual and/or engineers interested in faster processing speed for their PC, MacIntosh, or work station. Computer Systems Architects (CSA) currently sells a University Kit which allows multi-transputer systems to be added to Personal Computers for less than $500 per transputer. CSA also makes more sophisticated systems of up to 64 transputers with software configurable networks, offering a flexible support for the study of interconnection networks. I have experience with both of these systems and have used them in my classes.
The examples in this document are all written for the MS-DOS environment, on an IBM compatible. This makes this book unique as it provides the readers with a clear view of the many details involved in the interaction between the host and the parallel machine. Too frequently, such details are not covered in text books and are left to the users to discover on their own. This document makes it possible to design, program and integrate a sophisticated parallel program on a multiprocessor attached to an IBM PC or compatible.
The great majority of the books currently published in the field of parallel computation covers parallel algorithms. A drawback of such an approach is that the implementation of a simple algorithm may require radically different solutions depending on the target machine. For example, the efficient implementation of a histogram algorithm on a shared memory machine, on a message-passing machine, or on a data-parallel machine requires altogether different solutions. For this reason, learning parallel algorithms without the support of a specific machine is not sufficient to introduce someone to the challenges of parallel computation. Balancing the teaching of parallel algorithms with the programming of a parallel machine is paramount. Just as most computer science departments start first with a class on programming and data structures before studying algorithms, this html document takes the approach of first teaching how to program a message-passing parallel machine as an introduction to parallel algorithms. The ability to learn and understand parallel algorithms is greatly improved once one is already familiar with a multiprocessor machine. This freely-available web document, therefore, can be the perfect companion to a more abstract coverage of parallel algorithms in a class where the instructor will mix theory and general concepts along with a study of how they can be applied (successfully or not) in a message-passing environment.
The book is organized as follows:
(Statistics of accesses to different parts of the book are available here!)
The audience for this Web document on parallel programming
This book is intended primarily for two audiences: undergraduate computer science or computer engineering majors, and engineers or computer enthusiasts looking at effective and economical ways to boost the performance of their personal computer or workstations, or to learn the principles of parallel programming with a modest investment.
A place in the Computer Science curriculum
This document is written as the support for a one semester or one trimester course on parallel programming. Because the book assumes a background in C and an understanding of elementary algorithms, the readers should have taken a Computer Science I (high level language programming in Pascal or C) and Computer Science II (Data structures) courses, as well as a course on (single-processor) algorithms. A background in assembly language is not necessary, although the section detailing the hardware of the transputer would be more beneficial for readers familiar with Intel or Motorola microprocessors.
It is also conceivable to use this html text as the support for a course covering parallel programming and parallel algorithms. In this case, the instructor would most likely start with this book and familiarize the students with the transputer and parallel programming. As the level of programming sophistication increases, the instructor could use some of the applications of parallel algorithms introduced in this document as a starting point to a theoretical coverage of similar algorithms, their complexity, and range of application.
here to see the Table of Contents, or get the
accompanying software (R
EADME file, and
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