DocumentCode :
1513204
Title :
A tool to help tune where computation is performed
Author :
Eom, Hyeonsang ; Hollingsworth, Jeffrey K.
Author_Institution :
Dept. of Comput. Sci., Maryland Univ., College Park, MD, USA
Volume :
27
Issue :
7
fYear :
2001
fDate :
7/1/2001 12:00:00 AM
Firstpage :
618
Lastpage :
629
Abstract :
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
Keywords :
distributed programming; parallel programming; software metrics; software performance evaluation; distributed program; load balancing factor; parallel program; performance metric; tuning; Computational modeling; Current measurement; Distributed computing; Load management; Performance analysis; Performance evaluation; Performance gain; Programming profession; Testing; Time measurement;
fLanguage :
English
Journal_Title :
Software Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0098-5589
Type :
jour
DOI :
10.1109/32.935854
Filename :
935854
Link To Document :
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