The Impact of Improved Sparse Linear Solvers on Industrial Engineering Applications


                           Majdi Baddourah
                          Michael A. Heroux*
                           Eugene L. Poole
                            Chao Wu Yang
             Applications Division, Cray Research, Inc.

* - Presenter

Abstract

There are usually many factors that ultimately determine the quality 
of computer simulation for engineering applications.  Some of the most
important are the quality of the analytical model and approximation
scheme, the accuracy of the input data and the capability of the
computing resources.  However, in many engineering applications the 
characteristics of the sparse linear solver are the key factors in 
determining how complex a problem a given application code can solve.  
Therefore, the advent of a dramatically improved solver often brings 
with it dramatic improvements in our ability to do accurate and cost
effective computer simulations.

In this presentation we discuss the current status of sparse iterative
and direct solvers in several key industrial CFD and structures codes,
and show the impact that recent advances in linear solvers have made
on both our ability to perform challenging simulations and the cost of
those simulations.  We also present some of the current challenges we 
have and the constraints we face in trying to improve these solvers.
Finally, we discuss future requirements for sparse linear solvers on 
high performance architectures and try to indicate the opportunities
that exist if we can develop even more improvements in linear solver
capabilities.