A tool to help tune where computation is performed

TitleA tool to help tune where computation is performed
Publication TypeJournal Articles
Year of Publication2001
AuthorsEom H, Hollingsworth J
JournalIEEE Transactions on Software Engineering
Pagination618 - 629
Date Published2001/07//
ISBN Number0098-5589
KeywordsComputational modeling, Current measurement, Distributed computing, distributed program, distributed programming, load balancing factor, Load management, parallel program, parallel programming, Performance analysis, performance evaluation, Performance gain, performance metric, Programming profession, software metrics, software performance evaluation, Testing, Time measurement, tuning

We introduce a new performance metric, called load balancing factor (LBF), to assist programmers when evaluating different tuning alternatives. The LBF metric differs from traditional performance metrics since it is intended to measure the performance implications of a specific tuning alternative rather than quantifying where time is spent in the current version of the program. A second unique aspect of the metric is that it provides guidance about moving work within a distributed or parallel program rather than reducing it. A variation of the LBF metric can also be used to predict the performance impact of changing the underlying network. The LBF metric is computed incrementally and online during the execution of the program to be tuned. We also present a case study that shows that our metric can accurately predict the actual performance gains for a test suite of six programs