Shared Memory Optimization

Shared Memory Optimization is a computational strategy within GPU computing that enhances performance by minimizing data access latency through efficient allocation, organization, and synchronization of on-chip memory resources shared among parallel processing threads.

75

Publications

2.5K

Citations

228

Authors

97

Institutions

Publications per year

2017–2026

14

Authors

228

  1. WM
    Wenjing Ma

    The Ohio State University, United States

    3 publications · 47 citations

    3

    h-index

  2. SM
    Satoshi Matsuoka

    Tokyo Institute of Technology, Japan

    3 publications · 259 citations

    3

    h-index

  3. GA
    Gagan Agrawal

    The Ohio State University, United States

    3 publications · 97 citations

    3

    h-index

  4. DE
    David E. Keyes

    King Abdullah University of Science and Technology, Saudi Arabia

    2 publications · 32 citations

    2

    h-index

  5. PO
    Philippe O. A. Navaux

    Universidade Federal do Rio Grande do Sul, Brazil

    2 publications · 32 citations

    2

    h-index

1–5 of 228

Venues

  1. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 4 publications · 80 citations

    4

    h-index

  2. arXiv (Cornell University)

    Repository · 2 publications · 158 citations

    2

    h-index

  3. 2

    h-index

  4. The Journal of Supercomputing

    2 publications · 27 citations

    2

    h-index

  5. Journal of Computing and Information Technology

    CIT · 1 publications · 12 citations

    1

    h-index

1–5