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

descriptionPublicationkeyboard_double_arrow_right Research , Article , Conference object 01 Jan 2019Publisher:The Eurographics AssociationJournal:Vision, Modeling and VisualizationFunded by:EC | CloudiFacturing

Authors: Mueller-Roemer, Johannes Sebastian; Stork, André; Fellner, Dieter W.;

doi: 10.2312/vmv.20191324

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

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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 5.5x. In comparison to cuSPARSE, we achieve speedups of up to 4.7x

CCS Concepts: Computing methodologies --> Massively parallel algorithms; Parallel programming languages; Mathematics of computing --> Computations on matrices

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

Vision, Modeling and Visualization

GPU

109

116

Related Organizations

TU Darmstadt
Germany

Keywords

Parallel programming languages, Massively parallel algorithms, Computations on matrices, Mathematics of computing, Computing methodologies

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