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Valerio Pascucci
University of Utah
307Publications
45H-index
7,091Citations
Publications 303
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Topological approaches to data analysis can answer complex questions about the number, connectivity, and scale of intrinsic features in scalar data. However, the global nature of many topological structures makes their computation challenging at scale, and thus often limits the size of data that can be processed. One key quality to achieving scalability and performance on modern architectures is data locality, i.e., a process operates on data that resides in a nearby memory system, avoiding freq...
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#1Jeffrey Mohlman (UofU: University of Utah)H-Index: 2
#2Samuel Leventhal (UofU: University of Utah)
Last.Mohamed E. Salama (Mayo Clinic)H-Index: 20
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#1Attila GyulassyH-Index: 17
#2Peer-Timo Bremer (LLNL: Lawrence Livermore National Laboratory)H-Index: 26
Last.Valerio PascucciH-Index: 45
view all 3 authors...
Topological techniques have proven to be a powerful tool in the analysis and visualization of large-scale scientific data. In particular, the Morse-Smale complex and its various components provide a rich framework for robust feature definition and computation. Consequently, there now exist a number of approaches to compute Morse-Smale complexes for large-scale data in parallel. However, existing techniques are based on discrete concepts which produce the correct topological structure but are kno...
3 CitationsSource
#1Sidharth Kumar (UAB: University of Alabama at Birmingham)H-Index: 6
#2Steve Petruzza (UofU: University of Utah)H-Index: 3
Last.Valerio Pascucci (UofU: University of Utah)H-Index: 45
view all 4 authors...
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#1Duong Hoang (UofU: University of Utah)H-Index: 1
#2Pavol Klacansky (UofU: University of Utah)H-Index: 3
Last.Valerio Pascucci (UofU: University of Utah)H-Index: 45
view all 6 authors...
There currently exist two dominant strategies to reduce data sizes in analysis and visualization: reducing the precision of the data, e.g., through quantization, or reducing its resolution, e.g., by subsampling. Both have advantages and disadvantages and both face fundamental limits at which the reduced information ceases to be useful. The paper explores the additional gains that could be achieved by combining both strategies. In particular, we present a common framework that allows us to study ...
1 CitationsSource
#1Will Usher (UofU: University of Utah)H-Index: 3
#2Silvio Rizzi (Argonne National Laboratory)H-Index: 11
Last.Valerio Pascucci (UofU: University of Utah)H-Index: 45
view all 9 authors...
As simulations grow in scale, the need for in situ analysis methods to handle the large data produced grows correspondingly. One desirable approach to in situ visualization is in transit visualization. By decoupling the simulation and visualization code, in transit approaches alleviate common difficulties with regard to the scalability of the analysis, ease of integration, usability, and impact on the simulation. We present libIS, a lightweight, flexible library which lowers the bar for using in...
1 CitationsSource
Oct 31, 2018 in EMNLP (Empirical Methods in Natural Language Processing)
#1Shusen Liu (LLNL: Lawrence Livermore National Laboratory)H-Index: 10
#2Tao Li (UofU: University of Utah)H-Index: 2
Last.Peer-Timo Bremer (LLNL: Lawrence Livermore National Laboratory)H-Index: 26
view all 6 authors...
6 CitationsSource
#1Jeffrey Mohlman (UofU: University of Utah)H-Index: 2
#2Samuel Leventhal (UofU: University of Utah)
Last.Mohamed E. Salama (Mayo Clinic)H-Index: 20
view all 6 authors...
Source
#1Harsh BhatiaH-Index: 7
#2Attila Gyulassy (Scientific Computing and Imaging Institute)H-Index: 1
Last.Peer-Timo Bremer (Scientific Computing and Imaging Institute)H-Index: 26
view all 6 authors...
6 CitationsSource
#1Harsh Bhatia (LLNL: Lawrence Livermore National Laboratory)H-Index: 7
#2Nikhil Jain (LLNL: Lawrence Livermore National Laboratory)H-Index: 14
Last.Peer-Timo Bremer (Scientific Computing and Imaging Institute)H-Index: 26
view all 7 authors...
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