Parallelism Granularity

Parallelism Granularity is a measure in parallel computing that classifies the scale of computational tasks relative to communication and synchronization overhead, distinguishing itself by quantifying the size of atomic work units executed concurrently within a parallel system.

78

Publications

4.1K

Citations

236

Authors

113

Institutions

Publications per year

2017–2026

7

Authors

236

  1. MR
    Mike Rainey

    University of Chicago, United States

    4 publications · 142 citations

    4

    h-index

  2. JR
    John Reppy

    University of Chicago, United States

    3 publications · 127 citations

    3

    h-index

  3. KH
    Kevin Hammond

    University of St Andrews, United Kingdom

    3 publications · 54 citations

    3

    h-index

  4. MF
    Matthew Fluet

    University of Chicago, United States

    3 publications · 127 citations

    3

    h-index

  5. AA
    Alex Aiken

    Stanford University, United States

    2 publications · 95 citations

    2

    h-index

1–5 of 236

Venues

  1. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 4 publications · 434 citations

    4

    h-index

  2. Proceedings of the IEEE

    2 publications · 113 citations

    2

    h-index

  3. ACM SIGPLAN Notices

    2 publications · 68 citations

    2

    h-index

  4. Parallel Processing Letters

    2 publications · 24 citations

    2

    h-index

  5. Journal of Symbolic Computation

    1 publications · 81 citations

    1

    h-index

1–5