Application Signature: a new way to predict application performance

dc.contributor.advisor John Gustafson
dc.contributor.advisor Gurpur Prabhu Todi, Rajat
dc.contributor.department Computer Science 2018-08-24T18:58:21.000 2020-06-30T08:13:19Z 2020-06-30T08:13:19Z Wed Jan 01 00:00:00 UTC 2003 2003-01-01
dc.description.abstract <p>Advances in digital computers have been spectacular but increasingly complex to model. Even the cycle-accurate simulators, which are costly to develop and run have questionable accuracy. This thesis provides a simple, accurate, scientifically proven, and analytic model to accurately predict the performance of real applications. The method creates two profiles as a function of time or problem sizes. The first profile, Hardware Signature, that reveals computer hardware speed, is obtained by running a universal benchmark, HINT or by running an analytical model, AHINT. The second profile, Application Signature (APPMAP), that divulges intrinsic application requirements, can be obtained by four different methods outlined in the thesis. The convolution of these two profiles are used to predict real application performance. The model was tested using 25000 performance measurements and was validated by determining Pearson's correlation, Spearman's rank correlation and maximum deviation from linearity. Furthermore, through the Hardware Signature of the analytical models, one can obtain precise answers to questions about optimum size of memory, caches, and the numerical precision for a given clock rate.</p>
dc.format.mimetype application/pdf
dc.identifier archive/
dc.identifier.articleid 2912
dc.identifier.contextkey 6131434
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath rtd/1913
dc.language.iso en
dc.source.bitstream archive/|||Fri Jan 14 21:52:49 UTC 2022
dc.subject.disciplines Computer Sciences
dc.subject.keywords Computer science
dc.title Application Signature: a new way to predict application performance
dc.type article
dc.type.genre dissertation
dspace.entity.type Publication
relation.isOrgUnitOfPublication f7be4eb9-d1d0-4081-859b-b15cee251456 dissertation Doctor of Philosophy
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