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International Conference on Parallel Processing and Applied Mathematics

PPAM 2015: Parallel Processing and Applied Mathematics pp 106–115Cite as

Parallel Algorithm for Quasi-Band Matrix-Matrix Multiplication

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9573))

Abstract

Sparse matrices arise in many practical scenarios. As a result, support for efficient operations such as multiplication of sparse matrices (spmm) is considered to be an important research area. Often, sparse matrices also exhibit particular characteristics that can be used towards better parallel algorithmics. In this paper, we focus on quasi-band sparse matrices that have a large majority of the non-zeros along the diagonals. We design and implement an efficient algorithm for multiplying two such matrices on a many-core architecture such as a GPU.

Our implementation outperforms the corresponding library implementation by a factor of 2x on average over a wide variety of quasi-band matrices from standard datasets. We analyze our performance over synthetic quasi-band matrices.

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Author information

Authors and Affiliations

  1. International Institute of Information Technology, Hyderabad, Gachibowli, Hyderabad, 500032, India

    Dharma Teja Vooturi & Kishore Kothapalli

Authors
  1. Dharma Teja Vooturi
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  2. Kishore Kothapalli
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Corresponding author

Correspondence to Dharma Teja Vooturi .

Editor information

Editors and Affiliations

  1. Czestochowa University of Technolog, Czestochowa, Poland

    Roman Wyrzykowski

  2. Department of Computer Science, University of Southern California, Marina Del Rey, California, USA

    Ewa Deelman

  3. Electrical Engineering & Comput. Science, University of Tennessee, Knoxville, Tennessee, USA

    Jack Dongarra

  4. Czestochowa University of Technology, Institute of Computer & Information Sci., Czestochowa, Poland

    Konrad Karczewski

  5. Department of Computer Science, AGH University of Science and Technology, Krakow, Poland

    Jacek Kitowski

  6. Systèmes d’informations, Big Data et Rec, AGH University of Science and Technology, Krakow, Poland

    Kazimierz Wiatr

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© 2016 Springer International Publishing Switzerland

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Vooturi, D.T., Kothapalli, K. (2016). Parallel Algorithm for Quasi-Band Matrix-Matrix Multiplication. In: Wyrzykowski, R., Deelman, E., Dongarra, J., Karczewski, K., Kitowski, J., Wiatr, K. (eds) Parallel Processing and Applied Mathematics. PPAM 2015. Lecture Notes in Computer Science(), vol 9573. Springer, Cham. https://doi.org/10.1007/978-3-319-32149-3_11

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  • DOI: https://doi.org/10.1007/978-3-319-32149-3_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-32148-6

  • Online ISBN: 978-3-319-32149-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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