The substantial effort of parallel programming is only justified if the resulting codes are adequately efficient. In this sense, all types of performance tuning are extremely important to parallel software development. With parallel programs, performance improvements are much more difficult to achieve than with con ventional (sequential) programs. One way to overcome this inherent difficulty is to bring in graphical tools.

When trying to visualize parallel programs, one is faced with a vast amount of relevant literature consisting of more than 100 articles in journals or confer- ence proceedings and dozens of software systems.

This book pursues two major goals: first, to cover recent developments in parallel program visualization techniques and tools, most of which have not yet been dealt with by text books; second, to demonstrate the application of specific visualization techniques and software tools to scientific parallel programs.

For this purpose, two prototypical problem areas have been chosen: (i) so- lution of initial value problems of ordinary differential equations - a notoriously difficult problem with respect to parallelization, and (ii) numerical integration - a problem which is seemingly easy to parallelize. In these two fields the advan tages of parallel program visualization are demonstrated. One representative software system - ParaGraph - is used to show how visualization techniques can contribute to experimental performance assessment and improvement.