Joint Schedule and Layout Autotuning for Sparse Matrices with Compound Entries on GPUs

Johannes Mueller-Roemer, André Stork, Dieter W. Fellner

Publikation: Beitrag in Buch/Bericht/KonferenzbandBeitrag in einem KonferenzbandBegutachtung


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 5:5x. In comparison to cuSPARSE, we achieve speedups of up to 4:7x.
TitelVision, Modeling, and Visualization
Herausgeber (Verlag)University of Rostock
ISBN (elektronisch)978-3-03868-098-7
PublikationsstatusVeröffentlicht - 2019


NameVision, Modeling, and Visualization / von/by Schulz, Hans-J\örg [Ed.] [et al.]. - European Association for Computer Graphics (Eurographics): University of Rostock. - 978-3-03868-098-7 (ISBN). - (2019)
Herausgeber (Verlag)University of Rostock


  • Digitized Work
  • (Interactive) simulation (SIM)
  • GPU computing
  • Linear systems
  • Code generation

Fields of Expertise

  • Information, Communication & Computing

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