Overcoming Load Imbalance for Irregular Sparse Matrices | Zendy

Goran Flegar | Zendy; Hartwig Anzt | Zendy

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Overcoming Load Imbalance for Irregular Sparse Matrices

Author(s) -

Goran Flegar,

Hartwig Anzt

Publication year - 2017

Publication title -

repository kitopen (karlsruhe institute of technology)

Language(s) - English

Resource type - Conference proceedings

ISBN - 978-1-4503-5136-2

DOI - 10.1145/3149704.3149767

Subject(s) - kernel (algebra) , computer science , parallel computing , sparse matrix , implementation , cuda , matrix (chemical analysis) , computational science , mathematics , programming language , physics , materials science , quantum mechanics , combinatorics , composite material , gaussian

In this paper we propose a load-balanced GPU kernel for computing the sparse matrix vector (SpMV) product. Making heavy use of the latest GPU programming features, we also enable satisfying performance for irregular and unbalanced matrices. In a performance comparison using 400 test matrices we reveal the new kernel being superior to the most popular SpMV implementations.

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