000872819 001__ 872819
000872819 005__ 20250314084118.0
000872819 0247_ $$2doi$$a10.1109/TPDS.2019.2896993
000872819 037__ $$aFZJ-2020-00291
000872819 082__ $$a004
000872819 1001_ $$00000-0001-7238-7353$$aShudler, Sergei$$b0
000872819 245__ $$aEngineering Algorithms for Scalability through Continuous Validation of Performance Expectations
000872819 260__ $$aNew York, NY$$bIEEE$$c2019
000872819 3367_ $$2DRIVER$$aarticle
000872819 3367_ $$2DataCite$$aOutput Types/Journal article
000872819 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1621428593_24928
000872819 3367_ $$2BibTeX$$aARTICLE
000872819 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000872819 3367_ $$00$$2EndNote$$aJournal Article
000872819 500__ $$aBitte Post-Print ergänzen
000872819 520__ $$aMany libraries in the HPC field use sophisticated algorithms with clear theoretical scalability expectations. However, hardware constraints or programming bugs may sometimes render these expectations inaccurate or even plainly wrong. While algorithm and performance engineers have already been advocating the systematic combination of analytical performance models with practical measurements for a very long time, we go one step further and show how this comparison can become part of automated testing procedures. The most important applications of our method include initial validation, regression testing, and benchmarking to compare implementation and platform alternatives. Advancing the concept of performance assertions, we verify asymptotic scaling trends rather than precise analytical expressions, relieving the developer from the burden of having to specify and maintain very fine-grained and potentially non-portable expectations. In this way, scalability validation can be continuously applied throughout the whole development cycle with very little effort. Using MPI and parallel sorting algorithms as examples, we show how our method can help uncover non-obvious limitations of both libraries and underlying platforms.
000872819 536__ $$0G:(DE-HGF)POF3-511$$a511 - Computational Science and Mathematical Methods (POF3-511)$$cPOF3-511$$fPOF III$$x0
000872819 536__ $$0G:(DE-Juel1)jzam11_20091101$$aScalable Performance Analysis of Large-Scale Parallel Applications (jzam11_20091101)$$cjzam11_20091101$$fScalable Performance Analysis of Large-Scale Parallel Applications$$x1
000872819 536__ $$0G:(DE-Juel-1)ATMLPP$$aATMLPP - ATML Parallel Performance (ATMLPP)$$cATMLPP$$x2
000872819 588__ $$aDataset connected to CrossRef
000872819 7001_ $$0P:(DE-HGF)0$$aBerens, Yannick$$b1
000872819 7001_ $$0P:(DE-HGF)0$$aCalotoiu, Alexandru$$b2
000872819 7001_ $$0P:(DE-HGF)0$$aHoefler, Torsten$$b3
000872819 7001_ $$0P:(DE-Juel1)140202$$aStrube, Alexandre$$b4$$eCorresponding author
000872819 7001_ $$00000-0001-6595-3599$$aWolf, Felix$$b5
000872819 773__ $$0PERI:(DE-600)2027774-X$$a10.1109/TPDS.2019.2896993$$gVol. 30, no. 8, p. 1768 - 1785$$n8$$p1768 - 1785$$tIEEE transactions on parallel and distributed systems$$v30$$x1045-9219$$y2019
000872819 8564_ $$uhttps://juser.fz-juelich.de/record/872819/files/08632716.pdf$$yRestricted
000872819 8564_ $$uhttps://juser.fz-juelich.de/record/872819/files/08632716.pdf?subformat=pdfa$$xpdfa$$yRestricted
000872819 909CO $$ooai:juser.fz-juelich.de:872819$$pextern4vita
000872819 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)140202$$aForschungszentrum Jülich$$b4$$kFZJ
000872819 9131_ $$0G:(DE-HGF)POF3-511$$1G:(DE-HGF)POF3-510$$2G:(DE-HGF)POF3-500$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bKey Technologies$$lSupercomputing & Big Data$$vComputational Science and Mathematical Methods$$x0
000872819 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline
000872819 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bIEEE T PARALL DISTR : 2017
000872819 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS
000872819 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search
000872819 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC
000872819 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List
000872819 915__ $$0StatID:(DE-HGF)0110$$2StatID$$aWoS$$bScience Citation Index
000872819 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection
000872819 915__ $$0StatID:(DE-HGF)0111$$2StatID$$aWoS$$bScience Citation Index Expanded
000872819 915__ $$0StatID:(DE-HGF)1160$$2StatID$$aDBCoverage$$bCurrent Contents - Engineering, Computing and Technology
000872819 915__ $$0StatID:(DE-HGF)9900$$2StatID$$aIF < 5
000872819 920__ $$lyes
000872819 980__ $$ajournal
000872819 980__ $$aEDITORS
000872819 980__ $$aI:(DE-Juel1)JSC-20090406
000872819 980__ $$aI:(DE-82)080012_20140620
000872819 9801_ $$aEXTERN4VITA