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Using renderscript and RCUDA for compute intensive tasks on mobile devices: a case study

dc.contributor.authorKemp, Roelof
dc.contributor.authorPalmer, Nicholas
dc.contributor.authorKielmann, Thilo
dc.contributor.authorBal, Henri
dc.contributor.authorAarts, Bastiaan
dc.contributor.authorGhuloum, Anwar
dc.contributor.editorWagner, Stefan
dc.contributor.editorLichter, Horst
dc.date.accessioned2018-10-24T10:00:05Z
dc.date.available2018-10-24T10:00:05Z
dc.date.issued2013
dc.description.abstractThe processing power of mobile devices is continuously increasing. In this paper we perform a case study in which we assess three different programming models that can be used to leverage this processing power for compute intensive tasks. We use an imaging algorithm and compare a reference implementation of this algorithm based on OpenCV with a multi threaded RenderScript implementation and an implementation based on computation offloading with Remote CUDA. Experiments show that on a modern Tegra 3 quad core device a multi threaded implementation can achieve a 2.2 speed up factor at the same energy cost, whereas computation offloading does neither lead to speed ups nor energy savings.en
dc.identifier.isbn978-3-88579-609-1
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/17380
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofSoftware Engineering 2013 - Workshopband
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-215
dc.titleUsing renderscript and RCUDA for compute intensive tasks on mobile devices: a case studyen
dc.typeText/Conference Paper
gi.citation.endPage318
gi.citation.publisherPlaceBonn
gi.citation.startPage305
gi.conference.date26. Februar-1. März 2013
gi.conference.locationAachen
gi.conference.sessiontitleRegular Research Papers

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