Show simple item record

dc.contributor.authorKivioja, Markus
dc.contributor.authorMönkölä, Sanna
dc.contributor.authorRossi, Tuomo
dc.date.accessioned2022-08-17T07:53:39Z
dc.date.available2022-08-17T07:53:39Z
dc.date.issued2022
dc.identifier.citationKivioja, M., Mönkölä, S., & Rossi, T. (2022). GPU-accelerated time integration of Gross-Pitaevskii equation with discrete exterior calculus. <i>Computer Physics Communications</i>, <i>278</i>, Article 108427. <a href="https://doi.org/10.1016/j.cpc.2022.108427" target="_blank">https://doi.org/10.1016/j.cpc.2022.108427</a>
dc.identifier.otherCONVID_150845054
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/82636
dc.description.abstractThe quantized vortices in superfluids are modeled by the Gross-Pitaevskii equation whose numerical time integration is instrumental in the physics studies of such systems. In this paper, we present a reliable numerical method and its efficient GPU-accelerated implementation for the time integration of the three-dimensional Gross-Pitaevskii equation. The method is based on discrete exterior calculus which allows us the usage of more versatile spatial discretization than traditional finite difference and spectral methods are applicable to. We discretize the problem using six different natural crystal structures and observe the correct choices of spatial tiling to decrease the truncation error and increase the reliability compared to Cartesian grids. We pay attention to the computational performance optimizations of the GPU implementation and measure speedups of up to 152-fold when compared to a reference CPU implementation. We parallelize the implementation further to multiple GPUs and show that 92% of the computation time can fully utilize the additional resources.en
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherElsevier BV
dc.relation.ispartofseriesComputer Physics Communications
dc.rightsCC BY 4.0
dc.titleGPU-accelerated time integration of Gross-Pitaevskii equation with discrete exterior calculus
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-202208174180
dc.contributor.laitosInformaatioteknologian tiedekuntafi
dc.contributor.laitosFaculty of Information Technologyen
dc.contributor.oppiaineLaskennallinen tiedefi
dc.contributor.oppiaineTutkintokoulutusfi
dc.contributor.oppiaineTietotekniikkafi
dc.contributor.oppiaineComputing, Information Technology and Mathematicsfi
dc.contributor.oppiaineComputational Scienceen
dc.contributor.oppiaineDegree Educationen
dc.contributor.oppiaineMathematical Information Technologyen
dc.contributor.oppiaineComputing, Information Technology and Mathematicsen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1
dc.description.reviewstatuspeerReviewed
dc.relation.issn0010-4655
dc.relation.volume278
dc.type.versionpublishedVersion
dc.rights.copyright© 2022 The Author(s).
dc.rights.accesslevelopenAccessfi
dc.subject.ysonumeerinen analyysi
dc.subject.ysonumeeriset menetelmät
dc.subject.ysoosittaisdifferentiaaliyhtälöt
dc.subject.ysosuprajuoksevuus
dc.subject.ysorinnakkaiskäsittely
dc.subject.ysomatemaattiset mallit
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p15833
jyx.subject.urihttp://www.yso.fi/onto/yso/p6588
jyx.subject.urihttp://www.yso.fi/onto/yso/p12392
jyx.subject.urihttp://www.yso.fi/onto/yso/p38777
jyx.subject.urihttp://www.yso.fi/onto/yso/p12682
jyx.subject.urihttp://www.yso.fi/onto/yso/p11401
dc.rights.urlhttps://creativecommons.org/licenses/by/4.0/
dc.relation.doi10.1016/j.cpc.2022.108427
dc.type.okmA1


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record

CC BY 4.0
Except where otherwise noted, this item's license is described as CC BY 4.0