001035001 001__ 1035001
001035001 005__ 20250203133237.0
001035001 0247_ $$2doi$$a10.1109/TPDS.2024.3406764
001035001 0247_ $$2datacite_doi$$a10.34734/FZJ-2025-00107
001035001 0247_ $$2WOS$$aWOS:001272190100002
001035001 037__ $$aFZJ-2025-00107
001035001 082__ $$a004
001035001 1001_ $$00000-0002-9174-5598$$aTarraf, Ahmad$$b0$$eCorresponding author
001035001 245__ $$aMalleability in Modern HPC Systems: Current Experiences, Challenges, and Future Opportunities
001035001 260__ $$aNew York, NY$$bIEEE$$c2024
001035001 3367_ $$2DRIVER$$aarticle
001035001 3367_ $$2DataCite$$aOutput Types/Journal article
001035001 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1736774242_23768
001035001 3367_ $$2BibTeX$$aARTICLE
001035001 3367_ $$2ORCID$$aJOURNAL_ARTICLE
001035001 3367_ $$00$$2EndNote$$aJournal Article
001035001 520__ $$aWith the increase of complex scientific simulations driven by workflows and heterogeneous workload profiles, managing system resources effectively is essential for improving performance and system throughput, especially due to trends like heterogeneous HPC and deeply integrated systems with on-chip accelerators. For optimal resource utilization, dynamic resource allocation can improve productivity across all system and application levels, by adapting the applications’ configurations to the system's resources. In this context, malleable jobs, which can change resources at runtime, can increase the system throughput and resource utilization while bringing various advantages for HPC users (e.g., shorter waiting time). Malleability has received much attention recently, even though it has been an active research area for more than two decades. This article presents the state-of-the-art of malleable implementations in HPC systems, targeting mainly malleability in compute and I/O resources. Based on our experiences, we state our current concerns and list future opportunities for research.
001035001 536__ $$0G:(DE-HGF)POF4-5122$$a5122 - Future Computing & Big Data Systems (POF4-512)$$cPOF4-512$$fPOF IV$$x0
001035001 536__ $$0G:(EU-Grant)955606$$aDEEP-SEA - DEEP – SOFTWARE FOR EXASCALE ARCHITECTURES (955606)$$c955606$$fH2020-JTI-EuroHPC-2019-1$$x1
001035001 536__ $$0G:(EU-Grant)956748$$aADMIRE - Adaptive multi-tier intelligent data manager for Exascale (956748)$$c956748$$fH2020-JTI-EuroHPC-2019-1$$x2
001035001 536__ $$0G:(EU-Grant)955701$$aTIME-X - TIME parallelisation: for eXascale computing and beyond (955701)$$c955701$$fH2020-JTI-EuroHPC-2019-1$$x3
001035001 536__ $$0G:(BMBF)16HPC047$$aVerbundprojekt: TIME-X - Parallelisierung zeitabhängiger Simulationen für das zukünftige Supercomputing (16HPC047)$$c16HPC047$$x4
001035001 536__ $$0G:(EU-Grant)956560$$aREGALE - An open architecture to equip next generation HPC applications with exascale capabilities (956560)$$c956560$$fH2020-JTI-EuroHPC-2019-1$$x5
001035001 588__ $$aDataset connected to CrossRef, Journals: juser.fz-juelich.de
001035001 7001_ $$00000-0002-2390-6716$$aSchreiber, Martin$$b1
001035001 7001_ $$00000-0001-5506-1431$$aCascajo, Alberto$$b2
001035001 7001_ $$00000-0001-6500-6786$$aBesnard, Jean-Baptiste$$b3
001035001 7001_ $$00000-0001-7398-3034$$aVef, Marc-André$$b4
001035001 7001_ $$00000-0001-9696-9382$$aHuber, Dominik$$b5
001035001 7001_ $$0P:(DE-Juel1)194671$$aHapp, Sonja$$b6$$ufzj
001035001 7001_ $$00000-0003-3083-2775$$aBrinkmann, André$$b7
001035001 7001_ $$00000-0002-8125-0049$$aSingh, David E.$$b8
001035001 7001_ $$0P:(DE-Juel1)194562$$aHoppe, Hans-Christian$$b9
001035001 7001_ $$00000-0002-1386-628X$$aMiranda, Alberto$$b10
001035001 7001_ $$00000-0002-3575-4617$$aPeña, Antonio J.$$b11
001035001 7001_ $$00009-0009-2759-2302$$aMachado, Rui$$b12
001035001 7001_ $$00000-0003-3682-9905$$aGarcia-Gasulla, Marta$$b13
001035001 7001_ $$00000-0001-9013-435X$$aSchulz, Martin$$b14
001035001 7001_ $$00000-0002-9392-0521$$aCarpenter, Paul$$b15
001035001 7001_ $$0P:(DE-Juel1)177796$$aPickartz, Simon$$b16
001035001 7001_ $$00009-0000-8455-5553$$aRotaru, Tiberiu$$b17
001035001 7001_ $$00000-0003-3654-7924$$aIserte, Sergio$$b18
001035001 7001_ $$00000-0002-3113-9166$$aLopez, Victor$$b19
001035001 7001_ $$00000-0003-4725-5097$$aEjarque, Jorge$$b20
001035001 7001_ $$00000-0002-5629-1957$$aSirwani, Heena$$b21
001035001 7001_ $$00000-0002-1413-4793$$aCarretero, Jesus$$b22
001035001 7001_ $$0P:(DE-Juel1)132299$$aWolf, Felix$$b23
001035001 773__ $$0PERI:(DE-600)2027774-X$$a10.1109/TPDS.2024.3406764$$gVol. 35, no. 9, p. 1551 - 1564$$n9$$p1551 - 1564$$tIEEE transactions on parallel and distributed systems$$v35$$x2161-9883$$y2024
001035001 8564_ $$uhttps://juser.fz-juelich.de/record/1035001/files/Malleability_in_Modern_HPC_Systems_Current_Experiences_Challenges_and_Future_Opportunities.pdf$$yOpenAccess
001035001 909CO $$ooai:juser.fz-juelich.de:1035001$$pdnbdelivery$$pec_fundedresources$$pVDB$$pdriver$$popen_access$$popenaire
001035001 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)194671$$aForschungszentrum Jülich$$b6$$kFZJ
001035001 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)194562$$aForschungszentrum Jülich$$b9$$kFZJ
001035001 9101_ $$0I:(DE-HGF)0$$6P:(DE-Juel1)177796$$aExternal Institute$$b16$$kExtern
001035001 9131_ $$0G:(DE-HGF)POF4-512$$1G:(DE-HGF)POF4-510$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5122$$aDE-HGF$$bKey Technologies$$lEngineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action$$vSupercomputing & Big Data Infrastructures$$x0
001035001 9141_ $$y2024
001035001 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2023-08-29
001035001 915__ $$0LIC:(DE-HGF)CCBY4$$2HGFVOC$$aCreative Commons Attribution CC BY 4.0
001035001 915__ $$0StatID:(DE-HGF)0113$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2023-08-29
001035001 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
001035001 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bIEEE T PARALL DISTR : 2022$$d2025-01-02
001035001 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2025-01-02
001035001 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2025-01-02
001035001 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search$$d2025-01-02
001035001 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC$$d2025-01-02
001035001 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2025-01-02
001035001 915__ $$0StatID:(DE-HGF)1160$$2StatID$$aDBCoverage$$bCurrent Contents - Engineering, Computing and Technology$$d2025-01-02
001035001 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2025-01-02
001035001 915__ $$0StatID:(DE-HGF)9905$$2StatID$$aIF >= 5$$bIEEE T PARALL DISTR : 2022$$d2025-01-02
001035001 9201_ $$0I:(DE-Juel1)JSC-20090406$$kJSC$$lJülich Supercomputing Center$$x0
001035001 9801_ $$aFullTexts
001035001 980__ $$ajournal
001035001 980__ $$aVDB
001035001 980__ $$aUNRESTRICTED
001035001 980__ $$aI:(DE-Juel1)JSC-20090406