Parallel Data Structures
Parallel Data Structures is a class of data organization schemes designed to enable concurrent access and modification by multiple processing elements, distinguished by their explicit support for parallelism through synchronization mechanisms and memory access patterns that ensure correctness and efficiency in shared or distributed memory systems.
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1K
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2017–2026
234
1.9K
Data Structures and Algorithms
Niklaus Wirth · Scientific American · 1984 · 1.4K citations
Parallel Data, Tools and Interfaces in OPUS
Jörg Tiedemann · Language Resources and Evaluation · 2012 · 1.3K citations
Richard E. Ladner, Michael J. Fischer · Journal of the ACM · 1980 · 1.3K citations · Full text
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Carnegie Mellon University
Pittsburgh, United States
34 h-index
139 publications
10.6K citations
The University of Texas at Austin
Austin, United States
29 h-index
92 publications
10.5K citations
University of California, Berkeley
Berkeley, United States
26 h-index
105 publications
12.3K citations
Stanford University
Stanford, United States
23 h-index
62 publications
4.3K citations
IBM (United States)
Armonk, United States
22 h-index
74 publications
7.2K citations
University of Illinois Urbana-Champaign
Urbana, United States
22 h-index
97 publications
6.5K citations
University of Maryland, College Park
College Park, United States
21 h-index
69 publications
12.5K citations
Massachusetts Institute of Technology
Cambridge, United States
21 h-index
57 publications
4.6K citations
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57 publications · 2.9K citations
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62 publications · 2.8K citations
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TPDS · 38 publications · 1.5K citations
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47 publications · 3.7K citations
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29 publications · 970 citations
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