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David Pugmire
Dave Pugmire
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2020 – today
- 2024
- [j20]Tushar M. Athawale
, Bryan Triana, Tanmay Kotha, Dave Pugmire
A Comparative Study of the Perceptual Sensitivity of Topological Visualizations to Feature Variations. IEEE Trans. Vis. Comput. Graph. 30(1): 1074-1084 (2024) - [c48]James Hammer, Tanner Hobson, David Pugmire, Scott Klasky, Kenneth Moreland, Jian Huang:
A Personalized AI Assistant For Intuition-Driven Visual Explorations. e-Science 2024: 1-10 - [c47]David Pugmire, Kenneth Moreland, Tushar M. Athawale, James Hammer, Jian Huang:
Top Research Challenges and Opportunities for Near Real-Time Extreme-Scale Visualization of Scientific Data. e-Science 2024: 1-6 - [i11]Tushar M. Athawale, Zhe Wang, David Pugmire, Kenneth Moreland, Qian Gong, Scott Klasky, Christopher R. Johnson, Paul Rosen:
Uncertainty Visualization of Critical Points of 2D Scalar Fields for Parametric and Nonparametric Probabilistic Models. CoRR abs/2407.18015 (2024) - [i10]Shanu Saklani, Chitwan Goel, Shrey Bansal, Zhe Wang, Soumya Dutta, Tushar M. Athawale, David Pugmire, Christopher R. Johnson:
Uncertainty-Informed Volume Visualization using Implicit Neural Representation. CoRR abs/2408.06018 (2024) - [i9]Robert Sisneros, Tushar M. Athawale, David Pugmire, Kenneth Moreland:
An Entropy-Based Test and Development Framework for Uncertainty Modeling in Level-Set Visualizations. CoRR abs/2409.08445 (2024) - 2023
- [j19]Abhishek Yenpure
State-of-the-Art Report on Optimizing Particle Advection Performance. Comput. Graph. Forum 42(3): 517-537 (2023) - [j18]Tushar M. Athawale, Christopher R. Johnson
Fiber Uncertainty Visualization for Bivariate Data With Parametric and Nonparametric Noise Models. IEEE Trans. Vis. Comput. Graph. 29(1): 613-623 (2023) - [c46]Zhe Wang, Tushar M. Athawale, Kenneth Moreland
FunMC2: A Filter for Uncertainty Visualization of Marching Cubes on Multi-Core Devices. EGPGV@EuroVis 2023: 13-23 - [c45]Andy Trinh, Shivam Sheth, Anil Gaihre, Caiwen Ding, Jieyang Chen, Feiyi Wang, David Pugmire, Scott Klasky, Hang Liu, Lipeng Wan:
Understanding Node Allocation on Leadership-Class Supercomputers with Graph Analytics. HPCC/DSS/SmartCity/DependSys 2023: 780-787 - [c44]Mark Bolstad
VTK-m: Visualization for the Exascale Era and Beyond. SIGGRAPH Talks 2023: 57:1-57:2 - [e1]Roxana Bujack, David Pugmire, Guido Reina:
23rd Eurographics Symposium on Parallel Graphics and Visualization, EGPGV@EuroVis 2023, Leipzig, Germany, June 12, 2023. Eurographics Association 2023, ISBN 978-3-03868-215-8 [contents] - [i8]Tushar M. Athawale, Bryan Triana, Tanmay Kotha, Dave Pugmire, Paul Rosen:
A Comparative Study of the Perceptual Sensitivity of Topological Visualizations to Feature Variations. CoRR abs/2307.08795 (2023) - 2022
- [j17]Eric Suchyta
The Exascale Framework for High Fidelity coupled Simulations (EFFIS): Enabling whole device modeling in fusion science. Int. J. High Perform. Comput. Appl. 36(1): 106-128 (2022) - [j16]Xin Liang
MGARD+: Optimizing Multilevel Methods for Error-Bounded Scientific Data Reduction. IEEE Trans. Computers 71(7): 1522-1536 (2022) - [j15]Ana Gainaru
Understanding the Impact of Data Staging for Coupled Scientific Workflows. IEEE Trans. Parallel Distributed Syst. 33(10): 4134-4147 (2022) - [c43]Eric Suchyta
Hybrid Analysis of Fusion Data for Online Understanding of Complex Science on Extreme Scale Computers. CLUSTER 2022: 218-229 - [c42]David Pugmire, Jian Huang, Kenneth Moreland, Scott Klasky:
The Need for Pervasive In Situ Analysis and Visualization (P-ISAV). ISC Workshops 2022: 306-316 - [c41]Mengjiao Han, Tushar M. Athawale, David Pugmire, Chris R. Johnson:
Accelerated Probabilistic Marching Cubes by Deep Learning for Time-Varying Scalar Ensembles. IEEE VIS (Short Papers) 2022: 155-159 - [i7]Abhishek Yenpure, Sudhanshu Sane, Roba Binyahib, David Pugmire, Christoph Garth, Hank Childs:
A Guide to Particle Advection Performance. CoRR abs/2201.08440 (2022) - [i6]Mengjiao Han, Tushar M. Athawale, David Pugmire, Chris R. Johnson:
Accelerated Probabilistic Marching Cubes by Deep Learning for Time-Varying Scalar Ensembles. CoRR abs/2207.07260 (2022) - [i5]Tushar M. Athawale, Chris R. Johnson, Sudhanshu Sane, David Pugmire:
Fiber Uncertainty Visualization for Bivariate Data With Parametric and Nonparametric Noise Models. CoRR abs/2207.11318 (2022) - 2021
- [j14]Francis J. Alexander
Co-design Center for Exascale Machine Learning Technologies (ExaLearn). Int. J. High Perform. Comput. Appl. 35(6): 598-616 (2021) - [j13]Kenneth Moreland
Minimizing development costs for efficient many-core visualization using MCD3. Parallel Comput. 108: 102834 (2021) - [c40]Roba Binyahib, David Pugmire, Hank Childs:
HyLiPoD: Parallel Particle Advection Via a Hybrid of Lifeline Scheduling and Parallelization-Over-Data. EGPGV@EuroVis 2021: 1-5 - [c39]Samuel D. Schwartz, Hank Childs, David Pugmire:
Machine Learning-Based Autotuning for Parallel Particle Advection. EGPGV@EuroVis 2021: 7-17 - [c38]Jieyang Chen
Accelerating Multigrid-based Hierarchical Scientific Data Refactoring on GPUs. IPDPS 2021: 859-868 - [c37]Xin Liang, Qian Gong
Error-controlled, progressive, and adaptable retrieval of scientific data with multilevel decomposition. SC 2021: 88 - [c36]Qian Gong
Maintaining Trust in Reduction: Preserving the Accuracy of Quantities of Interest for Lossy Compression. SMC 2021: 22-39 - [c35]David Pugmire
Fides: A General Purpose Data Model Library for Streaming Data. ISC Workshops 2021: 495-507 - [i4]Jieyang Chen, Lipeng Wan, Xin Liang, Ben Whitney, Qing Liu, Qian Gong, David Pugmire, Nicholas Thompson, Jong Youl Choi, Matthew Wolf, Todd S. Munson, Ian T. Foster, Scott Klasky:
Scalable Multigrid-based Hierarchical Scientific Data Refactoring on GPUs. CoRR abs/2105.12764 (2021) - 2020
- [j12]Guido Reina
The moving target of visualization software for an increasingly complex world. Comput. Graph. 87: 12-29 (2020) - [j11]Jeremy Logan, Mark Ainsworth, Chuck Atkins, Jieyang Chen, Jong Choi, Junmin Gu, James Kress, Greg Eisenhauer, Berk Geveci, William F. Godoy, Mark Kim, Tahsin M. Kurç, Qing Liu, Kshitij Mehta, George Ostrouchov, Norbert Podhorszki, David Pugmire, Eric Suchyta, Nicholas Thompson, Ozan Tugluk, Lipeng Wan, Ruonan Wang, Ben Whitney, Matthew Wolf, Kesheng Wu, Scott Klasky:
Extending the Publish/Subscribe Abstraction for High-Performance I/O and Data Management at Extreme Scale. IEEE Data Eng. Bull. 43(1): 35-46 (2020) - [j10]Hank Childs, Sean Ahern, James P. Ahrens, Andrew C. Bauer, Janine Bennett, E. Wes Bethel, Peer-Timo Bremer, Eric Brugger, Joseph Cottam, Matthieu Dorier, Soumya Dutta
A terminology for in situ visualization and analysis systems. Int. J. High Perform. Comput. Appl. 34(6) (2020) - [j9]William F. Godoy
ADIOS 2: The Adaptable Input Output System. A framework for high-performance data management. SoftwareX 12: 100561 (2020) - [c34]Roba Binyahib, David Pugmire, Abhishek Yenpure, Hank Childs:
Parallel Particle Advection Bake-Off for Scientific Visualization Workloads. CLUSTER 2020: 381-391 - [c33]James Kress, Matthew Larsen, Jong Choi, Mark Kim, Matthew Wolf, Norbert Podhorszki, Scott Klasky, Hank Childs, David Pugmire:
Comparing Time-to-Solution for In Situ Visualization Paradigms at Scale. LDAV 2020: 22-26 - [c32]David Pugmire, James Kress, Jieyang Chen, Hank Childs, Jong Choi, Dmitry Ganyushin, Berk Geveci, Mark Kim, Scott Klasky, Xin Liang, Jeremy Logan, Nicole Marsaglia, Kshitij Mehta, Norbert Podhorszki
Visualization as a Service for Scientific Data. SMC 2020: 157-174 - [c31]James Kress, Matthew Larsen, Jong Choi, Mark Kim, Matthew Wolf, Norbert Podhorszki
Opportunities for Cost Savings with In-Transit Visualization. ISC 2020: 146-165 - [i3]Nicholas Thompson, John Maddock, George Ostrouchov, Jeremy Logan, David Pugmire, Scott Klasky:
Towards 1ULP evaluation of Daubechies Wavelets. CoRR abs/2005.05424 (2020) - [i2]Jieyang Chen, Lipeng Wan, Xin Liang, Ben Whitney, Qing Liu, Dave Pugmire, Nicholas Thompson, Matthew Wolf, Todd S. Munson, Ian T. Foster, Scott Klasky:
Accelerating Multigrid-based Hierarchical Scientific Data Refactoring on GPUs. CoRR abs/2007.04457 (2020) - [i1]Xin Liang, Ben Whitney, Jieyang Chen, Lipeng Wan, Qing Liu, Dingwen Tao, James Kress, David Pugmire, Matthew Wolf, Norbert Podhorszki, Scott Klasky:
MGARD+: Optimizing Multi-grid Based Reduction for Efficient Scientific Data Management. CoRR abs/2010.05872 (2020)
2010 – 2019
- 2019
- [c30]Roba Binyahib
A Lifeline-Based Approach for Work Requesting and Parallel Particle Advection. LDAV 2019: 52-61 - [c29]Roba Binyahib
In situ particle advection via parallelizing over particles. ISAV@SC 2019: 29-33 - [c28]James Kress, Matthew Larsen, Jong Choi, Mark Kim, Matthew Wolf, Norbert Podhorszki
Comparing the Efficiency of In Situ Visualization Paradigms at Scale. ISC 2019: 99-117 - 2018
- [c27]Jong Youl Choi, Choong-Seock Chang
Coupling Exascale Multiphysics Applications: Methods and Lessons Learned. eScience 2018: 442-452 - [c26]David Pugmire, Abhishek Yenpure, Mark Kim, James Kress, Robert Maynard, Hank Childs, Bernd Hentschel:
Performance-Portable Particle Advection with VTK-m. EGPGV@EuroVis 2018: 45-55 - [c25]Mark Kim, Scott Klasky, David Pugmire:
Dense Texture Flow Visualization using Data-Parallel Primitives. EGPGV@EuroVis 2018: 57-61 - [c24]Scott Klasky, Matthew Wolf
A View from ORNL: Scientific Data Research Opportunities in the Big Data Age. ICDCS 2018: 1357-1368 - [c23]James Kress, Jong Choi, Scott Klasky, Michael Churchill
Binning Based Data Reduction for Vector Field Data of a Particle-In-Cell Fusion Simulation. ISC Workshops 2018: 215-229 - [c22]Mark Kim, James Kress, Jong Choi, Norbert Podhorszki
In Situ Analysis and Visualization of Fusion Simulations: Lessons Learned. ISC Workshops 2018: 230-242 - 2017
- [c21]Tao Lu
Canopus: A Paradigm Shift Towards Elastic Extreme-Scale Data Analytics on HPC Storage. CLUSTER 2017: 58-69 - [c20]Tao Lu, Eric Suchyta, Jong Youl Choi, Norbert Podhorszki, Scott Klasky, Qing Liu, David Pugmire, Matthew Wolf, Mark Ainsworth:
Canopus: Enabling Extreme-Scale Data Analytics on Big HPC Storage via Progressive Refactoring. HotStorage 2017 - [c19]Scott Klasky, Eric Suchyta
Exacution: Enhancing Scientific Data Management for Exascale. ICDCS 2017: 1927-1937 - [c18]Mark Kim, Tom Evans, Scott Klasky, David Pugmire:
In Situ Visualization of Radiation Transport Geometry. ISAV@SC 2017: 7-11 - [c17]David Pugmire, Ebru Bozdag, Matthieu Lefebvre, Jeroen Tromp
Pillars of the Mantle: Imaging the Interior of the Earth with Adjoint Tomography. PEARC 2017: 75:1-75:4 - 2016
- [j8]Kenneth Moreland, Christopher M. Sewell, William Usher
VTK-m: Accelerating the Visualization Toolkit for Massively Threaded Architectures. IEEE Computer Graphics and Applications 36(3): 48-58 (2016) - [j7]James Kress, Randy Michael Churchill
Preparing for In Situ Processing on Upcoming Leading-edge Supercomputers. Supercomput. Front. Innov. 3(4): 49-65 (2016) - [c16]David Pugmire, James Kress
Visualization and Analysis for Near-Real-Time Decision Making in Distributed Workflows. IPDPS Workshops 2016: 1007-1013 - [c15]Robert Sisneros, David Pugmire:
Tuned to Terrible: A Study of Parallel Particle Advection State of the Practice. IPDPS Workshops 2016: 1058-1067 - [c14]James Kress, David Pugmire, Scott Klasky, Hank Childs:
Visualization and Analysis Requirements for In Situ Processing for a Large-Scale Fusion Simulation Code. ISAV@SC 2016: 45-50 - [c13]Matthew Larsen, Cyrus Harrison, James Kress, David Pugmire, Jeremy S. Meredith, Hank Childs:
Performance modeling of in situ rendering. SC 2016: 276-287 - 2015
- [c12]James Kress
Loosely Coupled In Situ Visualization: A Perspective on Why It's Here to Stay. ISAV@SC 2015: 1-6 - 2013
- [j6]Dean N. Williams, Peer-Timo Bremer, Charles M. Doutriaux, John Patchett, Sean Williams, Galen M. Shipman, Ross Miller, David Pugmire, Brian E. Smith, Chad A. Steed
Ultrascale Visualization of Climate Data. Computer 46(9): 68-76 (2013) - [j5]Wei-Chen Chen, George Ostrouchov, David Pugmire, Prabhat, Michael F. Wehner
A Parallel EM Algorithm for Model-Based Clustering Applied to the Exploration of Large Spatio-Temporal Data. Technometrics 55(4): 513-523 (2013) - [c11]Roselyne Tchoua, Jong Youl Choi, Scott Klasky, Qing Liu, Jeremy Logan, Kenneth Moreland, Jingqing Mu, Manish Parashar, Norbert Podhorszki
ADIOS Visualization Schema: A First Step Towards Improving Interdisciplinary Collaboration in High Performance Computing. e-Science 2013: 27-34 - [c10]David Camp, Harinarayan Krishnan, David Pugmire, Christoph Garth
GPU Acceleration of Particle Advection Workloads in a Parallel, Distributed Memory Setting. EGPGV@Eurographics 2013: 1-8 - [c9]Hari Krishnan, Cyrus Harrison, Brad Whitlock, David Pugmire, Hank Childs:
Exploring Collaborative HPC Visualization Workflows using VisIt and Python. SciPy 2013: 65-69 - 2012
- [c8]Jeremy S. Meredith, Robert Sisneros, David Pugmire, Sean Ahern:
A distributed data-parallel framework for analysis and visualization algorithm development. GPGPU@ASPLOS 2012: 11-19 - [c7]Roselyne Tchoua, Hasan Abbasi, Scott Klasky, Qing Liu, Norbert Podhorszki, David Pugmire, Yuan Tian, Matthew Wolf:
Collaborative monitoring and visualization of HPC data. CTS 2012: 397-403 - [c6]Jong Youl Choi, Hasan Abbasi, David Pugmire, Norbert Podhorszki, Scott Klasky, Cristian Capdevila, Manish Parashar, Matthew Wolf, Judy Qiu, Geoffrey C. Fox:
Mining hidden mixture context with ADIOS-P to improve predictive pre-fetcher accuracy. eScience 2012: 1-8 - [c5]Jeremy S. Meredith, Sean Ahern, David Pugmire, Robert Sisneros:
EAVL: The Extreme-scale Analysis and Visualization Library. EGPGV@Eurographics 2012: 21-30 - [c4]David Camp, Christoph Garth
Parallel stream surface computation for large data sets. LDAV 2012: 39-47 - [p4]E. Wes Bethel, David Camp, Hank Childs, Christoph Garth
Hybrid Parallelism. High Performance Visualization 2012 - [p3]Hank Childs, Eric Brugger, Brad Whitlock, Jeremy S. Meredith, Sean Ahern, David Pugmire, Kathleen Biagas, Mark C. Miller, Cyrus Harrison, Gunther H. Weber, Hari Krishnan, Thomas Fogal, Allen R. Sanderson, Christoph Garth
VisIt. High Performance Visualization 2012 - [p2]Hank Childs, David Pugmire, Sean Ahern, Brad Whitlock, Mark Howison, Gunther H. Weber, E. Wes Bethel:
Visualization at Extreme Scale Concurrency. High Performance Visualization 2012 - [p1]David Pugmire, Tom Peterka, Christoph Garth
Parallel Integral Curves. High Performance Visualization 2012 - 2011
- [j4]David Camp, Christoph Garth
Streamline Integration Using MPI-Hybrid Parallelism on a Large Multicore Architecture. IEEE Trans. Vis. Comput. Graph. 17(11): 1702-1713 (2011) - [c3]David Pugmire, Paul Sutter, Paul M. Ricker, Hsiang-Yi (Karen) Yang, George Foreman:
Magnetic field outflows from active galactic nuclei. SC Companion 2011: 129-130 - 2010
- [j3]Hank Childs, David Pugmire, Sean Ahern, Brad Whitlock, Mark Howison
Extreme Scaling of Production Visualization Software on Diverse Architectures. IEEE Computer Graphics and Applications 30(3): 22-31 (2010) - [j2]Allen R. Sanderson, Guoning Chen
Analysis of Recurrent Patterns in Toroidal Magnetic Fields. IEEE Trans. Vis. Comput. Graph. 16(6): 1431-1440 (2010)
2000 – 2009
- 2009
- [c2]David Pugmire, Hank Childs, Christoph Garth
Scalable computation of streamlines on very large datasets. SC 2009 - 2007
- [j1]David Pugmire, Laura Monroe, Carolyn Connor Davenport, Andrew DuBois, David DuBois, Stephen Poole:
NPU-Based Image Compositing in a Distributed Visualization System. IEEE Trans. Vis. Comput. Graph. 13(4): 798-809 (2007)
1990 – 1999
- 1995
- [c1]Cindy Grimm
Visual Interfaces for Solids Modeling. ACM Symposium on User Interface Software and Technology 1995: 51-60
Coauthor Index
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last updated on 2024-10-15 21:34 CEST by the dblp team
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