Parallel Divide and Conquer is a computational algorithmic paradigm that extends the classical divide and conquer strategy by concurrently solving subproblems across multiple processing units, thereby reducing overall execution time through parallelization of recursive subdivisions.
147
Publications
6.9K
Citations
329
Authors
172
Institutions
Publications per year
2017–2026
21
Parents
Publications
147
Parallel tree contraction and its application
Gary L. Miller, John H. Reif · 1985 · 411 citations
Prefix sums and their applications
Guy E. Blelloch · Figshare · 2018 · 383 citations · Full text
1–5 of 147
Authors
329
- JD
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- CL
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- DS
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- CH
4
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- JD
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1–5 of 329
Institutions
172
University of California, Berkeley
Berkeley, United States
6 h-index
9 publications
548 citations
University of Southern California
Los Angeles, United States
5 h-index
19 publications
2.1K citations
Lawrence Berkeley National Laboratory
Berkeley, United States
5 h-index
18 publications
445 citations
University of Passau
Passau, Germany
5 h-index
8 publications
174 citations
University of Tennessee at Knoxville
Knoxville, United States
4 h-index
8 publications
272 citations
Calvin University
Grand Rapids, United States
4 h-index
4 publications
111 citations
University of Toronto
Toronto, Canada
4 h-index
7 publications
750 citations
The University of Tokyo
Tokyo, Japan
4 h-index
12 publications
610 citations
1–8 of 172
Venues
- ACM SIGPLAN Notices
7 publications · 112 citations
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- IEEE Transactions on Parallel and Distributed Systems
TPDS · 5 publications · 295 citations
5
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- Parallel Processing Letters
4 publications · 101 citations
4
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- arXiv (Cornell University)
Repository · 4 publications · 62 citations
4
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- IEEE Transactions on Computers
4 publications · 174 citations
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