Work-depth Analysis

Work-Depth Analysis is a theoretical framework in parallel computing that characterizes the performance of parallel algorithms by distinguishing the total computational effort (work) from the length of the critical path (depth), thereby enabling the analysis of both time complexity and parallelizability.

14

Publications

440

Citations

42

Authors

15

Institutions

Publications per year

2017–2026

8

Authors

42

  1. TH
    Torsten Hoefler

    ETH Zurich, Switzerland

    3 publications · 68 citations

    3

    h-index

  2. MB
    Maciej Besta

    ETH Zurich, Switzerland

    2 publications · 55 citations

    2

    h-index

  3. AS
    Aaron Sidford

    Stanford University, United States

    2 publications · 33 citations

    2

    h-index

  4. GE
    Guy E. Blelloch

    Carnegie Mellon University, United States

    2 publications · 175 citations

    2

    h-index

  5. AJ
    Arun Jambulapati

    Stanford University, United States

    2 publications · 33 citations

    2

    h-index

1–5 of 42

Venues

  1. arXiv (Cornell University)

    Repository · 2 publications · 27 citations

    2

    h-index

  2. ACM SIGPLAN Notices

    1 publications · 34 citations

    1

    h-index

  3. Organization Studies

    1 publications · 28 citations

    1

    h-index

  4. International Journal of Manufacturing Research

    IJMR · 1 publications · 25 citations

    1

    h-index

  5. PubMed

    Repository · 1 publications · 13 citations

    1

    h-index

1–5