Mueller-Roemer, J. S. ; Stork, A. ; Fellner, D. (2020)
Analysis of Schedule and Layout Tuning for Sparse Matrices With Compound Entries on GPUs.
In: Computer Graphics Forum, 39 (6)
doi: 10.1111/cgf.13957
Artikel, Bibliographie
Kurzbeschreibung (Abstract)
Large sparse matrices with compound entries, i.e. complex and quaternionic matrices as well as matrices with dense blocks, are a core component of many algorithms in geometry processing, physically based animation and other areas of computer graphics. We generalize several matrix layouts and apply joint schedule and layout autotuning to improve the performance of the sparse matrix-vector product on massively parallel graphics processing units. Compared to schedule tuning without layout tuning, we achieve speedups of up to 5.5×. In comparison to cuSPARSE, we achieve speedups of up to 4.7×.
Typ des Eintrags: | Artikel |
---|---|
Erschienen: | 2020 |
Autor(en): | Mueller-Roemer, J. S. ; Stork, A. ; Fellner, D. |
Art des Eintrags: | Bibliographie |
Titel: | Analysis of Schedule and Layout Tuning for Sparse Matrices With Compound Entries on GPUs |
Sprache: | Englisch |
Publikationsjahr: | 1 September 2020 |
Verlag: | Wiley & Sons Ltd. |
Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Computer Graphics Forum |
Jahrgang/Volume einer Zeitschrift: | 39 |
(Heft-)Nummer: | 6 |
DOI: | 10.1111/cgf.13957 |
Kurzbeschreibung (Abstract): | Large sparse matrices with compound entries, i.e. complex and quaternionic matrices as well as matrices with dense blocks, are a core component of many algorithms in geometry processing, physically based animation and other areas of computer graphics. We generalize several matrix layouts and apply joint schedule and layout autotuning to improve the performance of the sparse matrix-vector product on massively parallel graphics processing units. Compared to schedule tuning without layout tuning, we achieve speedups of up to 5.5×. In comparison to cuSPARSE, we achieve speedups of up to 4.7×. |
Freie Schlagworte: | General Purpose Computation on Graphics Processing Unit (GPGPU), Parallel computing, Matrix operations |
Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Graphisch-Interaktive Systeme |
Hinterlegungsdatum: | 07 Mai 2020 09:47 |
Letzte Änderung: | 04 Feb 2022 12:37 |
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Suche nach Titel in: | TUfind oder in Google |
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