000872622 001__ 872622
000872622 005__ 20210130004236.0
000872622 0247_ $$2Handle$$a2128/23824
000872622 037__ $$aFZJ-2020-00114
000872622 1001_ $$0P:(DE-Juel1)169856$$aMorgenstern, Laura$$b0$$eCorresponding author$$ufzj
000872622 1112_ $$aPlatform for Advanced Scientific Computing$$cZurich$$d2019-06-12 - 2019-06-14$$gPASC19$$wSwitzerland
000872622 245__ $$aTasking Meets GPUs:Fighting Deadlocks and Other Monsters
000872622 260__ $$c2019
000872622 3367_ $$033$$2EndNote$$aConference Paper
000872622 3367_ $$2BibTeX$$aINPROCEEDINGS
000872622 3367_ $$2DRIVER$$aconferenceObject
000872622 3367_ $$2ORCID$$aCONFERENCE_POSTER
000872622 3367_ $$2DataCite$$aOutput Types/Conference Poster
000872622 3367_ $$0PUB:(DE-HGF)24$$2PUB:(DE-HGF)$$aPoster$$bposter$$mposter$$s1578902033_31746$$xAfter Call
000872622 520__ $$aTask parallelism is omnipresent these days; whether in data mining or machine learning, for matrix factorization or even molecular dynamics. Despite the successof task parallelism on CPUs, there is currently no performant way to exploit task parallelism of synchronization-critical algorithms on GPUs.Hence, our goal is the development of a task-based programming model to exploit fine-grained task parallelism on heterogeneous hardware.
000872622 536__ $$0G:(DE-HGF)POF3-511$$a511 - Computational Science and Mathematical Methods (POF3-511)$$cPOF3-511$$fPOF III$$x0
000872622 536__ $$0G:(DE-Juel1)PHD-NO-GRANT-20170405$$aPhD no Grant - Doktorand ohne besondere Förderung (PHD-NO-GRANT-20170405)$$cPHD-NO-GRANT-20170405$$x1
000872622 7001_ $$0P:(DE-Juel1)157750$$aBeckmann, Andreas$$b1$$ufzj
000872622 7001_ $$0P:(DE-Juel1)132152$$aKabadshow, Ivo$$b2$$ufzj
000872622 7001_ $$0P:(DE-HGF)0$$aWerner -> Werner, Matthias$$b3
000872622 8564_ $$uhttps://juser.fz-juelich.de/record/872622/files/PASC2019.pdf$$yOpenAccess
000872622 8564_ $$uhttps://juser.fz-juelich.de/record/872622/files/PASC2019.pdf?subformat=pdfa$$xpdfa$$yOpenAccess
000872622 909CO $$ooai:juser.fz-juelich.de:872622$$pdriver$$pVDB$$popen_access$$popenaire
000872622 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)169856$$aForschungszentrum Jülich$$b0$$kFZJ
000872622 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)157750$$aForschungszentrum Jülich$$b1$$kFZJ
000872622 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)132152$$aForschungszentrum Jülich$$b2$$kFZJ
000872622 9131_ $$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$$x0
000872622 9141_ $$y2019
000872622 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
000872622 9201_ $$0I:(DE-Juel1)JSC-20090406$$kJSC$$lJülich Supercomputing Center$$x0
000872622 9801_ $$aFullTexts
000872622 980__ $$aposter
000872622 980__ $$aVDB
000872622 980__ $$aUNRESTRICTED
000872622 980__ $$aI:(DE-Juel1)JSC-20090406