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OpenMP, OpenMP/MPI, and CUDA/MPI C programs for solving the time-dependent dipolar Gross–Pitaevskii equation

dc.contributor.authorLončar, Vladimir
dc.contributor.authorYoung, Luis E.S. [UNESP]
dc.contributor.authorŠkrbić, Srdjan
dc.contributor.authorMuruganandam, Paulsamy
dc.contributor.authorAdhikari, Sadhan K. [UNESP]
dc.contributor.authorBalaž, Antun
dc.contributor.institutionUniversity of Belgrade
dc.contributor.institutionUniversidad Santo Tomás
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionUniversity of Novi Sad
dc.contributor.institutionBharathidasan University
dc.date.accessioned2018-12-11T17:07:02Z
dc.date.available2018-12-11T17:07:02Z
dc.date.issued2016-12-01
dc.description.abstractWe present new versions of the previously published C and CUDA programs for solving the dipolar Gross–Pitaevskii equation in one, two, and three spatial dimensions, which calculate stationary and non-stationary solutions by propagation in imaginary or real time. Presented programs are improved and parallelized versions of previous programs, divided into three packages according to the type of parallelization. First package contains improved and threaded version of sequential C programs using OpenMP. Second package additionally parallelizes three-dimensional variants of the OpenMP programs using MPI, allowing them to be run on distributed-memory systems. Finally, previous three-dimensional CUDA-parallelized programs are further parallelized using MPI, similarly as the OpenMP programs. We also present speedup test results obtained using new versions of programs in comparison with the previous sequential C and parallel CUDA programs. The improvements to the sequential version yield a speedup of 1.1–1.9, depending on the program. OpenMP parallelization yields further speedup of 2–12 on a 16-core workstation, while OpenMP/MPI version demonstrates a speedup of 11.5–16.5 on a computer cluster with 32 nodes used. CUDA/MPI version shows a speedup of 9–10 on a computer cluster with 32 nodes.en
dc.description.affiliationScientific Computing Laboratory Center for the Study of Complex Systems Institute of Physics Belgrade University of Belgrade, Pregrevica 118
dc.description.affiliationDepartamento de Ciencias Básicas Universidad Santo Tomás, 150001 Tunja
dc.description.affiliationInstituto de Física Teórica UNESP—Universidade Estadual Paulista, 01.140-70 São Paulo
dc.description.affiliationDepartment of Mathematics and Informatics Faculty of Sciences University of Novi Sad, Trg Dositeja Obradovića 4
dc.description.affiliationSchool of Physics Bharathidasan University, Palkalaiperur Campus
dc.description.affiliationUnespInstituto de Física Teórica UNESP—Universidade Estadual Paulista, 01.140-70 São Paulo
dc.format.extent190-196
dc.identifierhttp://dx.doi.org/10.1016/j.cpc.2016.07.029
dc.identifier.citationComputer Physics Communications, v. 209, p. 190-196.
dc.identifier.doi10.1016/j.cpc.2016.07.029
dc.identifier.file2-s2.0-84991746823.pdf
dc.identifier.issn0010-4655
dc.identifier.scopus2-s2.0-84991746823
dc.identifier.urihttp://hdl.handle.net/11449/173642
dc.language.isoeng
dc.relation.ispartofComputer Physics Communications
dc.relation.ispartofsjr1,729
dc.rights.accessRightsAcesso aberto
dc.sourceScopus
dc.subjectBose–Einstein condensate
dc.subjectC program
dc.subjectCUDA program
dc.subjectDipolar atoms
dc.subjectGPU
dc.subjectGross–Pitaevskii equation
dc.subjectMPI
dc.subjectOpenMP
dc.subjectSplit-step Crank–Nicolson scheme
dc.titleOpenMP, OpenMP/MPI, and CUDA/MPI C programs for solving the time-dependent dipolar Gross–Pitaevskii equationen
dc.typeArtigo
dspace.entity.typePublication
unesp.author.orcid0000-0002-5435-1688[6]
unesp.campusUniversidade Estadual Paulista (UNESP), Instituto de Física Teórica (IFT), São Paulopt

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