Full metadata record
DC FieldValueLanguage
dc.contributor.authorRuda, Dustin-
dc.contributor.authorTurek, Stefan-
dc.contributor.authorRibbrock, Dirk-
dc.contributor.authorZajac, Peter-
dc.date.accessioned2021-07-06T12:14:54Z-
dc.date.available2021-07-06T12:14:54Z-
dc.date.issued2021-06-
dc.identifier.issn2190-1767-
dc.identifier.urihttp://hdl.handle.net/2003/40294-
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-22167-
dc.description.abstractIt is demonstrated that modern accelerator hardware specialized in AI, e.g., “next gen GPUs” equipped with Tensor Cores, can be profitably used in finite element simulations by means of a new hardware-oriented method to solve linear systems arising from Poisson’s equation in 2D. We consider the NVIDIA Tesla V100 Tensor Core GPU with a peak performance of 125 TFLOP/s, that is only achievable in half precision and if operations with high arithmetic intensity, such as dense matrix multiplications, are executed, though. Its computing power can be exploited to a great extent by the new method based on “prehandling” without loss of accuracy. We obtain a significant reduction of computing time compared to a standard geometric multigrid solver on standard x64 hardware.en
dc.language.isoen-
dc.relation.ispartofseriesErgebnisberichte des Instituts für Angewandte Mathematik;645-
dc.subject.ddc610-
dc.titleA Proof of Concept for Very Fast Finite Element Poisson Solvers on Accelerator Hardwareen
dc.typeText-
dc.type.publicationtypepreprint-
dcterms.accessRightsopen access-
eldorado.secondarypublicationfalse-
Appears in Collections:Ergebnisberichte des Instituts für Angewandte Mathematik

Files in This Item:
File Description SizeFormat 
Ergebnisbericht Nr. 645.pdfDNB210.31 kBAdobe PDFView/Open


This item is protected by original copyright



This item is protected by original copyright rightsstatements.org