Structural Prediction Models for
High-Performance Distributed Applications
Jennifer Schopf
Proceedings of the Cluster Computing Conference
(CCC '97), March 1997. 
Also available as UCSD CSE Technical Report #CS97-528.


We present a structural  performance  model to predict an
application's performance on a set of distributed resources.
We  decompose application performance in accordance with
the structure of the application, that is, into interacting
component  models  that  correspond  to component sub-tasks.
Then, using the application profile and available  information
as guides,  we  select models for each component appropriately.
This allows different modeling approaches for different
application components as needed.  As a proof-of-concept,
we have implemented this approach for two  distributed
applications, a master-slave genetic algorithm  code  and
a  red-black  stencil   successive while demonstrating the
flexibility this framework allows.