Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ruda, Dustin | - |
dc.contributor.author | Turek, Stefan | - |
dc.contributor.author | Ribbrock, Dirk | - |
dc.contributor.author | Zajac, Peter | - |
dc.date.accessioned | 2021-07-06T12:14:54Z | - |
dc.date.available | 2021-07-06T12:14:54Z | - |
dc.date.issued | 2021-06 | - |
dc.identifier.issn | 2190-1767 | - |
dc.identifier.uri | http://hdl.handle.net/2003/40294 | - |
dc.identifier.uri | http://dx.doi.org/10.17877/DE290R-22167 | - |
dc.description.abstract | It 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.iso | en | - |
dc.relation.ispartofseries | Ergebnisberichte des Instituts für Angewandte Mathematik;645 | - |
dc.subject.ddc | 610 | - |
dc.title | A Proof of Concept for Very Fast Finite Element Poisson Solvers on Accelerator Hardware | en |
dc.type | Text | - |
dc.type.publicationtype | preprint | - |
dcterms.accessRights | open access | - |
eldorado.secondarypublication | false | - |
Appears in Collections: | Ergebnisberichte des Instituts für Angewandte Mathematik |
Files in This Item:
File | Description | Size | Format | |
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Ergebnisbericht Nr. 645.pdf | DNB | 210.31 kB | Adobe PDF | View/Open |
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