CUDA programs for solving the time-dependent dipolar Gross–Pitaevskii equation in an anisotropic trap

Detalhes bibliográficos
Autor(a) principal: Lončar, Vladimir
Data de Publicação: 2016
Outros Autores: Balaž, Antun, Bogojević, Aleksandar, Škrbić, Srdjan, Muruganandam, Paulsamy, Adhikari, Sadhan K. [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1016/j.cpc.2015.11.014
http://hdl.handle.net/11449/172360
Resumo: In this paper we present new versions of previously published numerical programs for solving the dipolar Gross-Pitaevskii (GP) equation including the contact interaction in two and three spatial dimensions in imaginary and in real time, yielding both stationary and non-stationary solutions. New versions of programs were developed using CUDA toolkit and can make use of Nvidia GPU devices. The algorithm used is the same split-step semi-implicit Crank-Nicolson method as in the previous version (Kishor Kumar et al., 2015), which is here implemented as a series of CUDA kernels that compute the solution on the GPU. In addition, the Fast Fourier Transform (FFT) library used in the previous version is replaced by cuFFT library, which works on CUDA-enabled GPUs. We present speedup test results obtained using new versions of programs and demonstrate an average speedup of 12-25, depending on the program and input size.
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spelling CUDA programs for solving the time-dependent dipolar Gross–Pitaevskii equation in an anisotropic trapBose–Einstein condensateC programCUDA programDipolar atomsGPUGross–Pitaevskii equationPartial differential equationReal- and imaginary-time propagationSplit-step Crank–Nicolson schemeIn this paper we present new versions of previously published numerical programs for solving the dipolar Gross-Pitaevskii (GP) equation including the contact interaction in two and three spatial dimensions in imaginary and in real time, yielding both stationary and non-stationary solutions. New versions of programs were developed using CUDA toolkit and can make use of Nvidia GPU devices. The algorithm used is the same split-step semi-implicit Crank-Nicolson method as in the previous version (Kishor Kumar et al., 2015), which is here implemented as a series of CUDA kernels that compute the solution on the GPU. In addition, the Fast Fourier Transform (FFT) library used in the previous version is replaced by cuFFT library, which works on CUDA-enabled GPUs. We present speedup test results obtained using new versions of programs and demonstrate an average speedup of 12-25, depending on the program and input size.Scientific Computing Laboratory Institute of Physics Belgrade University of Belgrade, Pregrevica 118Department of Mathematics and Informatics Faculty of Sciences University of Novi Sad, Trg Dositeja Obradovića 4School of Physics Bharathidasan University, Palkalaiperur CampusInstituto de Física Teórica UNESP–Universidade Estadual Paulista, 01.140-70 São PauloInstituto de Física Teórica UNESP–Universidade Estadual Paulista, 01.140-70 São PauloUniversity of BelgradeUniversity of Novi SadBharathidasan UniversityUniversidade Estadual Paulista (Unesp)Lončar, VladimirBalaž, AntunBogojević, AleksandarŠkrbić, SrdjanMuruganandam, PaulsamyAdhikari, Sadhan K. [UNESP]2018-12-11T16:59:54Z2018-12-11T16:59:54Z2016-03-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article406-410application/pdfhttp://dx.doi.org/10.1016/j.cpc.2015.11.014Computer Physics Communications, v. 200, p. 406-410.0010-4655http://hdl.handle.net/11449/17236010.1016/j.cpc.2015.11.0142-s2.0-849520256822-s2.0-84952025682.pdfScopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengComputer Physics Communications1,729info:eu-repo/semantics/openAccess2023-10-30T06:05:49Zoai:repositorio.unesp.br:11449/172360Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462023-10-30T06:05:49Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv CUDA programs for solving the time-dependent dipolar Gross–Pitaevskii equation in an anisotropic trap
title CUDA programs for solving the time-dependent dipolar Gross–Pitaevskii equation in an anisotropic trap
spellingShingle CUDA programs for solving the time-dependent dipolar Gross–Pitaevskii equation in an anisotropic trap
Lončar, Vladimir
Bose–Einstein condensate
C program
CUDA program
Dipolar atoms
GPU
Gross–Pitaevskii equation
Partial differential equation
Real- and imaginary-time propagation
Split-step Crank–Nicolson scheme
title_short CUDA programs for solving the time-dependent dipolar Gross–Pitaevskii equation in an anisotropic trap
title_full CUDA programs for solving the time-dependent dipolar Gross–Pitaevskii equation in an anisotropic trap
title_fullStr CUDA programs for solving the time-dependent dipolar Gross–Pitaevskii equation in an anisotropic trap
title_full_unstemmed CUDA programs for solving the time-dependent dipolar Gross–Pitaevskii equation in an anisotropic trap
title_sort CUDA programs for solving the time-dependent dipolar Gross–Pitaevskii equation in an anisotropic trap
author Lončar, Vladimir
author_facet Lončar, Vladimir
Balaž, Antun
Bogojević, Aleksandar
Škrbić, Srdjan
Muruganandam, Paulsamy
Adhikari, Sadhan K. [UNESP]
author_role author
author2 Balaž, Antun
Bogojević, Aleksandar
Škrbić, Srdjan
Muruganandam, Paulsamy
Adhikari, Sadhan K. [UNESP]
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv University of Belgrade
University of Novi Sad
Bharathidasan University
Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Lončar, Vladimir
Balaž, Antun
Bogojević, Aleksandar
Škrbić, Srdjan
Muruganandam, Paulsamy
Adhikari, Sadhan K. [UNESP]
dc.subject.por.fl_str_mv Bose–Einstein condensate
C program
CUDA program
Dipolar atoms
GPU
Gross–Pitaevskii equation
Partial differential equation
Real- and imaginary-time propagation
Split-step Crank–Nicolson scheme
topic Bose–Einstein condensate
C program
CUDA program
Dipolar atoms
GPU
Gross–Pitaevskii equation
Partial differential equation
Real- and imaginary-time propagation
Split-step Crank–Nicolson scheme
description In this paper we present new versions of previously published numerical programs for solving the dipolar Gross-Pitaevskii (GP) equation including the contact interaction in two and three spatial dimensions in imaginary and in real time, yielding both stationary and non-stationary solutions. New versions of programs were developed using CUDA toolkit and can make use of Nvidia GPU devices. The algorithm used is the same split-step semi-implicit Crank-Nicolson method as in the previous version (Kishor Kumar et al., 2015), which is here implemented as a series of CUDA kernels that compute the solution on the GPU. In addition, the Fast Fourier Transform (FFT) library used in the previous version is replaced by cuFFT library, which works on CUDA-enabled GPUs. We present speedup test results obtained using new versions of programs and demonstrate an average speedup of 12-25, depending on the program and input size.
publishDate 2016
dc.date.none.fl_str_mv 2016-03-01
2018-12-11T16:59:54Z
2018-12-11T16:59:54Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1016/j.cpc.2015.11.014
Computer Physics Communications, v. 200, p. 406-410.
0010-4655
http://hdl.handle.net/11449/172360
10.1016/j.cpc.2015.11.014
2-s2.0-84952025682
2-s2.0-84952025682.pdf
url http://dx.doi.org/10.1016/j.cpc.2015.11.014
http://hdl.handle.net/11449/172360
identifier_str_mv Computer Physics Communications, v. 200, p. 406-410.
0010-4655
10.1016/j.cpc.2015.11.014
2-s2.0-84952025682
2-s2.0-84952025682.pdf
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Computer Physics Communications
1,729
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 406-410
application/pdf
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
_version_ 1799964752347136000

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