000844645 001__ 844645
000844645 005__ 20210129233024.0
000844645 0247_ $$2doi$$a10.3233/978-1-61499-843-3-369
000844645 037__ $$aFZJ-2018-02040
000844645 041__ $$aEnglish
000844645 1001_ $$0P:(DE-Juel1)156619$$aBaumeister, P. F.$$b0$$eCorresponding author
000844645 1112_ $$aParallel Computing$$cBologna$$d2017-09-12 - 2017-09-15$$gParCo2017$$wItaly
000844645 245__ $$aStrategies for Forward Modelling of Infrared Radiative Transfer on GPUs
000844645 260__ $$aAmsterdam$$bIOS Press$$c2018
000844645 29510 $$aParallel Computing is Everywhere
000844645 300__ $$a369 - 380
000844645 3367_ $$2ORCID$$aCONFERENCE_PAPER
000844645 3367_ $$033$$2EndNote$$aConference Paper
000844645 3367_ $$2BibTeX$$aINPROCEEDINGS
000844645 3367_ $$2DRIVER$$aconferenceObject
000844645 3367_ $$2DataCite$$aOutput Types/Conference Paper
000844645 3367_ $$0PUB:(DE-HGF)8$$2PUB:(DE-HGF)$$aContribution to a conference proceedings$$bcontrib$$mcontrib$$s1540208922_3608
000844645 3367_ $$0PUB:(DE-HGF)7$$2PUB:(DE-HGF)$$aContribution to a book$$mcontb
000844645 4900_ $$aAdvances in Parallel Computing$$v32
000844645 520__ $$aSatellite-based remote sensing in the mid-infrared spectral region can deliver a wealth of information on pressure, temperature, clouds and aerosols, and trace gas concentrations in the atmosphere. Interpreting the satellite measurements requires to solve an inverse modelling problem based on variational methods and a forward model evaluating the radiative transfer equations. As state-of-the-art satellite measurement campaigns require Petascale systems to process the data in due time, graphical processing units are employed for the high-throughput problem of computing the forward model for a given atmospheric state. We explore features of the considered architecture as well as relevant performance signatures of the different implementations to improve our understanding on opportunities for efficient exploitation of GPU-accelerated architectures based on the POWER2processor for this class of applications. Scalability is a key aspect as the application is known to scale well on massively-parallel architectures.
000844645 536__ $$0G:(DE-HGF)POF3-511$$a511 - Computational Science and Mathematical Methods (POF3-511)$$cPOF3-511$$fPOF III$$x0
000844645 536__ $$0G:(DE-HGF)POF3-513$$a513 - Supercomputer Facility (POF3-513)$$cPOF3-513$$fPOF III$$x1
000844645 7001_ $$0P:(DE-HGF)0$$aRombach, B.$$b1
000844645 7001_ $$0P:(DE-Juel1)176815$$aHater, Thorsten$$b2$$ufzj
000844645 7001_ $$0P:(DE-Juel1)129121$$aGriessbach, S.$$b3
000844645 7001_ $$0P:(DE-Juel1)129125$$aHoffmann, L.$$b4
000844645 7001_ $$0P:(DE-HGF)0$$aBühler, M.$$b5
000844645 7001_ $$0P:(DE-Juel1)144441$$aPleiter, D.$$b6
000844645 773__ $$a10.3233/978-1-61499-843-3-369
000844645 909CO $$ooai:juser.fz-juelich.de:844645$$pVDB
000844645 9141_ $$y2018
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000844645 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)129125$$aForschungszentrum Jülich$$b4$$kFZJ
000844645 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)144441$$aForschungszentrum Jülich$$b6$$kFZJ
000844645 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
000844645 9131_ $$0G:(DE-HGF)POF3-513$$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$$vSupercomputer Facility$$x1
000844645 9201_ $$0I:(DE-Juel1)JSC-20090406$$kJSC$$lJülich Supercomputing Center$$x0
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