Parallel Algorithm Complexity
Parallel Algorithm Complexity is the computational complexity measure that characterizes the time, processor, and communication resource requirements of a parallel algorithm as a function of input size, distinguishing it from sequential algorithm complexity by accounting for concurrent execution and inter-processor interactions in parallel computing models.
607
Publications
29.2K
Citations
1.2K
Authors
480
Institutions
Publications per year
2017–2026
67
Parents
607
A fast parallel algorithm for thinning digital patterns
Tingwei Zhang, Ching Y. Suen · Communications of the ACM · 1984 · 2.7K citations · Full text
An O(logn) parallel connectivity algorithm
Yossi Shiloach, Uzi Vishkin · Journal of Algorithms · 1982 · 598 citations
1–5 of 607
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480
Stanford University
Stanford, United States
16 h-index
34 publications
1.5K citations
Purdue University West Lafayette
West Lafayette, United States
14 h-index
27 publications
978 citations
University of Southern California
Los Angeles, United States
13 h-index
27 publications
718 citations
Carnegie Mellon University
Pittsburgh, United States
12 h-index
22 publications
951 citations
IBM Research - Thomas J. Watson Research Center
Yorktown Heights, United States
11 h-index
13 publications
528 citations

University of Toronto
Toronto, Canada
11 h-index
15 publications
643 citations
University of Maryland, College Park
College Park, United States
10 h-index
12 publications
405 citations
University of Illinois Urbana-Champaign
Urbana, United States
10 h-index
14 publications
900 citations
1–8 of 480
39 publications · 2.4K citations
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22 publications · 1.5K citations
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TPDS · 22 publications · 487 citations
14
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15 publications · 329 citations
12
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12 publications · 702 citations
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