Parallel Matrix Factorization

Parallel Matrix Factorization is a computational method in numerical linear algebra that decomposes a matrix into constituent factors by simultaneously leveraging multiple processing units to accelerate the factorization process, thereby distinguishing it from sequential matrix factorization techniques through its inherent concurrency and distributed workload management.

324

Publications

16.7K

Citations

708

Authors

311

Institutions

Publications per year

2017–2026

52

Authors

708

  1. JD
    Jack Dongarra

    University of Tennessee at Knoxville, United States

    21 publications · 675 citations

    15

    h-index

  2. RA
    Robert A. Geijn

    The University of Texas at Austin, United States

    7 publications · 274 citations

    7

    h-index

  3. JL
    Julien Langou

    University of Tennessee at Knoxville, United States

    6 publications · 142 citations

    6

    h-index

  4. JD
    James Demmel

    University of California, Berkeley, United States

    6 publications · 350 citations

    6

    h-index

  5. AP
    Alex Pothen

    Purdue University West Lafayette, United States

    6 publications · 1.9K citations

    6

    h-index

1–5 of 708

Venues

  1. Parallel Computing

    17 publications · 542 citations

    14

    h-index

  2. arXiv (Cornell University)

    Repository · 10 publications · 825 citations

    10

    h-index

  3. 10

    h-index

  4. SIAM Journal on Scientific Computing

    9 publications · 391 citations

    9

    h-index

  5. ACM Transactions on Mathematical Software

    TOMS · 7 publications · 267 citations

    7

    h-index

1–5