%0 Journal Article %J IEEE Transactions on Software Engineering %D 2001 %T A tool to help tune where computation is performed %A Eom, Hyeonsang %A Hollingsworth, Jeffrey K %K Computational modeling %K Current measurement %K Distributed computing %K distributed program %K distributed programming %K load balancing factor %K Load management %K parallel program %K parallel programming %K Performance analysis %K performance evaluation %K Performance gain %K performance metric %K Programming profession %K software metrics %K software performance evaluation %K Testing %K Time measurement %K tuning %X 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 %B IEEE Transactions on Software Engineering %V 27 %P 618 - 629 %8 2001/07// %@ 0098-5589 %G eng %N 7 %R 10.1109/32.935854