Skeleton Based Performance Prediction on Shared Networks
by S. Sodhi and J. Subhlok


The performance skeleton of an application is a short running program
 whose performance in any scenario reflects the performance of the 
application it represents. Such a skeleton can be employed to quickly 
estimate the performance of a large application under existing network
 and node sharing. This paper presents and validates a framework for
 automatic construction of performance skeletons of parallel 
applications. The approach is based on capturing the compute and 
communication behavior of an executing application, summarizing this 
behavior and then generating a synthetic skeleton program based on the 
summarized information. We demonstrate that automatically generated 
performance skeletons take an order of magnitude less time to execute
 than the application they represent, yet predict the application
 execution time with reasonable accuracy. For the NAS benchmark suite, 
we observed that the average error in predicting the execution time was
 6%. This research is motivated by the problem of performance  driven 
resource selection in shared network and grid environments.