NPAC Technical Report SCCS-580
A Scalable Paradigm for Effectively-Dense Matrix Formulated Applications
Gang Cheng, Geoffrey Fox, Ken Hawick
Submitted December 1 1993
Abstract
There is a class of problems in computational science and
engineering which require formulation in full matrix form and which
are generally solved as dense matrices either because they are dense
or because the sparsity can not be easily exploited. Problems such as
those posed by computational electromagnetics, computational chemistry
and some quantum physics applications frequently fall into this class.
It is not sufficient just to solve the matrix problem for these
applications as other components of the calculation are usually of
equal computational load on current computer systems, and these
components are consequently of equal importance to the end user of the
application. We describe a general method for programming such
applications using a combination of distributed computing systems and
of more powerful back-end compute resources to schedule the components
of such applications. We show how this not only improves
computational performance but by making more memory available, allows
hitherto impracticably large problems to be run. We illustrate this
problem paradigm and our method of solution with problems in
electromagnetics, chemistry and physics, and give a detailed
performance analysis of a typical electromagnetics application. We
discuss a method for scheduling the computational components using the
Application Visualisation System (AVS).