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Register-based implementation of the sparse general matrix-matrix multiplication on GPUs

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Published:10 February 2018Publication History
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Abstract

General sparse matrix-matrix multiplication (SpGEMM) is an essential building block in a number of applications. In our work, we fully utilize GPU registers and shared memory to implement an efficient and load balanced SpGEMM in comparison with the existing implementations.

References

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  1. Register-based implementation of the sparse general matrix-matrix multiplication on GPUs

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    • Published in

      cover image ACM SIGPLAN Notices
      ACM SIGPLAN Notices  Volume 53, Issue 1
      PPoPP '18
      January 2018
      426 pages
      ISSN:0362-1340
      EISSN:1558-1160
      DOI:10.1145/3200691
      Issue’s Table of Contents
      • cover image ACM Conferences
        PPoPP '18: Proceedings of the 23rd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming
        February 2018
        442 pages
        ISBN:9781450349826
        DOI:10.1145/3178487

      Copyright © 2018 Owner/Author

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 10 February 2018

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