Parameterizable Data Paths
Parameterizable Data Paths is a computational framework in which data flow architectures are designed to enable dynamic reconfiguration of processing elements and interconnects through configurable parameters, distinguishing it from static data paths by supporting adaptable execution patterns in response to varying algorithmic or hardware requirements.
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307
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31
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11
Institutions
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2017–2026
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A new parameterizable power macro-model for datapath components
Gerd Jochens, Lars Kruse, Eike Schmidt et al. · 1999 · 32 citations
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IMEC
Leuven, Belgium
3 h-index
10 publications
309 citations
Carnegie Mellon University
Pittsburgh, United States
2 h-index
6 publications
96 citations
Oldenburger Institut für Informatik
Oldenburg, Germany
2 h-index
8 publications
184 citations
Princeton University
Princeton, United States
1 h-index
4 publications
76 citations
Philips (Netherlands)
Amsterdam, The Netherlands
1 h-index
1 publications
48 citations

Université Toulouse III - Paul Sabatier
Toulouse, France
1 h-index
1 publications
27 citations
University of California, Berkeley
Berkeley, United States
1 h-index
2 publications
96 citations
University of Southern California
Los Angeles, United States
1 h-index
2 publications
84 citations
1–8 of 11
1 publications · 27 citations
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1 publications · 21 citations
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1 publications · 27 citations
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1 publications · 48 citations
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Conference · 1 publications · 34 citations
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