Memory Coalescing

Memory Coalescing is a memory access optimization technique in GPU computing, wherein consecutive threads in a warp access adjacent memory locations, enabling the aggregation of multiple memory requests into fewer transactions by exploiting spatial locality and thereby increasing memory bandwidth utilization.

37

Publications

1.2K

Citations

130

Authors

64

Institutions

Publications per year

2017–2026

12

Authors

130

  1. AJ
    Adrián J. Lew

    Stanford University, United States

    2 publications · 215 citations

    2

    h-index

  2. SJ
    Sanjay Jinturkar

    University of Virginia, United States

    2 publications · 103 citations

    2

    h-index

  3. ED
    Eric Darve

    Stanford University, United States

    2 publications · 215 citations

    2

    h-index

  4. JW
    Jack W. Davidson

    University of Virginia, United States

    2 publications · 103 citations

    2

    h-index

  5. XX
    Xing Xie

    Microsoft Research Asia (China), China

    2 publications · 76 citations

    2

    h-index

1–5 of 130

Venues

  1. South African Computer Journal

    SACJ · 1 publications · 20 citations

    1

    h-index

  2. Tsinghua Science & Technology

    1 publications · 13 citations

    1

    h-index

  3. ACM SIGPLAN Notices

    1 publications · 14 citations

    1

    h-index

  4. ACM Transactions on Architecture and Code Optimization

    TACO · 1 publications · 12 citations

    1

    h-index

  5. The Journal of Supercomputing

    1 publications · 15 citations

    1

    h-index

1–5