\section{Institute for Software Technology and Parallel Systems, University of
Vienna (PPS --- Programming Languages, Parallel Systems)} 

One of the most fundamental challenges facing computer science 
today is the need to develop the algorithms and programming tools
required to harness the vast computing power of modern 
high-performance computers.  
The commercially available machines that 
fall into this (roughly defined) class today include vector and 
array computers, parallel architectures  with a large number
of processors, and networks of high-performance workstations.
These machines provide their users with a peak performance of 
up to 10 billion floating point operations per second, thus 
opening the way for the solution of problems which seemed 
computationally quite out of reach until
recently, and spawning interest in a whole range of new problems.

High-performance computers have become a fundamental tool of science.  While 
computers have long been used to organize and control scientific 
experiments and analyze their results, the new machines can do much 
more than that: they play an important role in theoretical science 
too, enabling scientists to construct and test models in their 
search for theories to describe natural  phenomena.

Our interest focusses on programming environments for high-performance
computers, in particular on the following areas:
\begin{itemize}
\item  automatic parallelization
\item   performance analysis
\item   advanced compiling techniques 
\item use of knowledge-based methods
for the intelligent support of program transformation strategies
\item  intelligent man-machine interfaces
\end{itemize} 

We believe that these areas are of 
vital importance if high-performance computers are to be effectively 
utilized.



