Parallel Sparse Linear Algebra

Parallel Sparse Linear Algebra is a computational framework that enables the distributed execution of linear algebra operations on sparse matrices through parallel processing techniques, distinguishing itself by optimizing scalability and efficiency in high-performance computing environments.

780

Publications

40.9K

Citations

1.5K

Authors

457

Institutions

Publications per year

2017–2026

110

Authors

1.5K

  1. JD
    Jack Dongarra

    University of Tennessee at Knoxville, United States

    37 publications · 1.9K citations

    21

    h-index

  2. JD
    James Demmel

    University of California, Berkeley, United States

    19 publications · 2.9K citations

    18

    h-index

  3. ID
    Iain Duff

    Rutherford Appleton Laboratory, United Kingdom

    16 publications · 831 citations

    14

    h-index

  4. RA
    Robert A. Geijn

    The University of Texas at Austin, United States

    15 publications · 1.6K citations

    13

    h-index

  5. WL
    Weifeng Liu

    China University of Petroleum, Beijing, China

    12 publications · 748 citations

    12

    h-index

1–5 of 1.5K

Venues

  1. SIAM Journal on Scientific Computing

    34 publications · 3.3K citations

    28

    h-index

  2. Parallel Computing

    76 publications · 3K citations

    28

    h-index

  3. ACM Transactions on Mathematical Software

    TOMS · 30 publications · 2.2K citations

    22

    h-index

  4. Journal of Parallel and Distributed Computing

    19 publications · 1.5K citations

    15

    h-index

  5. arXiv (Cornell University)

    Repository · 14 publications · 398 citations

    11

    h-index

1–5