Dataflow Optimization
Dataflow Optimization is a methodological framework within dataflow modeling that systematically enhances the efficiency, performance, or resource utilization of data processing systems by transforming and reorganizing dataflow representations according to specified optimization criteria.
152
Publications
7.4K
Citations
509
Authors
182
Institutions
Publications per year
2017–2026
46
Parents
152
Tyler Akidau, Robert Bradshaw, Craig Chambers et al. · Proceedings of the VLDB Endowment · 2015 · 577 citations
A Survey of Accelerator Architectures for Deep Neural Networks
Yiran Chen, Yuan Xie, Linghao Song et al. · Engineering · 2020 · 358 citations · Full text
DRESC: a retargetable compiler for coarse-grained reconfigurable architectures
Bingfeng Mei, Serge Vernalde, Diederik Verkest et al. · 2003 · 207 citations
1–5 of 152
509
University of Maryland, College Park, United States
7 publications · 224 citations
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4
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4
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4
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1–5 of 509
182
École Polytechnique Fédérale de Lausanne
Lausanne, Switzerland
8 h-index
28 publications
508 citations
Massachusetts Institute of Technology
Cambridge, United States
7 h-index
12 publications
1K citations
Hewlett-Packard (United States)
Palo Alto, United States
6 h-index
14 publications
609 citations
Technische Universität Berlin
Berlin, Germany
5 h-index
16 publications
1K citations
Universitat Politècnica de Catalunya
Barcelona, Spain
5 h-index
15 publications
681 citations
University of Maryland, College Park
College Park, United States
5 h-index
12 publications
416 citations
Humboldt-Universität zu Berlin
Berlin, Germany
4 h-index
9 publications
574 citations

Imperial College London
London, United Kingdom
4 h-index
10 publications
507 citations
1–8 of 182
5 publications · 276 citations
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PVLDB · 5 publications · 970 citations
5
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FGCS · 4 publications · 56 citations
4
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3 publications · 53 citations
3
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3 publications · 59 citations
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