THE LINUX FOUNDATION PROJECTS

Publications

Please use when referencing Viskores in scientific publications. (bib file)

Note that some of the older publications refer to predecessors of Viskores where software was inherited from.

  1. Kenneth Moreland, Jefferson Amstutz, Tushar M. Athawale, Vicente Bolea, Mark Bolstad, Hank Childs, Berk Geveci, Cyrus Harrison, Matthew Larsen, Li-Ta Lo, Nicole Marsaglia, Manish Mathai, David Pugmire, Silvio Rizzi, Spiros Tsalikis, and Gunther H. Weber. Viskores: Integrating Parallel Scientific Visualization Research into Applications, In VisGap – The Gap between Visualization Research and Visualization Software, June 2026. doi:10.2312/visgap.20261000.
  2. Makani Buckley, Kenneth Moreland, and Hank Childs. Rasterization with Data-Parallel Primitives, In Eurographics Symposium on Parallel Graphics and Visualization (EGPGV), June 2026. doi:10.2312/egpgv.20261000.

  3. Spiros Tsalikis, Will Schroeder, Daniel Szafir, and Kenneth Moreland. Memory-Aware External Facelist Calculation: A Data-Parallel Atomic Hash Counting Approach, IEEE Transactions on Visualization and Computer Graphics, 32(6):1–10, June 2026. doi:10.1109/TVCG.2026.3694435.

  4. Mingzhe Li, Hamish Carr, Oliver Rübel, Bei Wang, and Gunther H. Weber. Extremely Scalable Distributed Computation of Contour Trees via Pre-Simplification, In Proceedings of the 15th IEEE Symposium on Large Data Analysis and Visualization (LDAV), November 2025. doi:10.1109/LDAV68558.2025.00005.

  5. Timbwaoga A. J. Ouermi, Eric Li, Kenneth Moreland, Dave Pugmire, Chris R. Johnson, and Tushar M. Athawale. Efficient Probabilistic Visualization of Local Divergence of 2D Vector Fields with Independent Gaussian Uncertainty, In 2025 IEEE Workshop on Uncertainty Visualization: Unraveling Relationships of Uncertainty, AI, and Decision-Making, pages 12–16, November 2025. Winner best paper. doi:10.1109/UncertaintyVisualization68947.2025.00006.

  6. Zhe Wang, Kenneth Moreland, Matthew Larsen, James Kress, Hank Childs, and David Pugmire. Parallelize Over Data Particle Advection: Participation, Ping Pong Particles, and Overhead, IEEE Transactions on Visualization and Computer Graphics, 31(10):7795–7808, October 2025. doi:10.1109/TVCG.2025.3557453.

  7. Mingzhe Li, Hamish Carr, Oliver Rübel, Bei Wang, and Gunther H. Weber. Distributed Augmentation, Hypersweeps, and Branch Decomposition of Contour Trees for Scientific Exploration, IEEE Transactions on Visualization and Computer Graphics, 31(1):152–162, September 2025. doi:10.1109/TVCG.2024.3456322.

  8. Tushar M. Athawale, Zhe Wang, David Pugmire, Kenneth Moreland, Qian Gong, Scott Klasky, Chris R. Johnson, and Paul Rosen. Uncertainty Visualization of Critical Points of 2D Scalar Fields for Parametric and Nonparametric Probabilistic Models, IEEE Transactions on Visualization and Computer Graphics, 31(1):108–118, January 2025. doi:10.1109/TVCG.2024.3456393.

  9. Kenneth Moreland. The Viskores User’s Guide, Oak Ridge National Laboratory, Technical Report ORNL/TM-2025/4175, 2025. https://viskores.readthedocs.io/en/v1.1.1/.

  10. Gautam Hari, Nrushad Joshi, Zhe Wang, Qian Gong, Dave Pugmire, Kenneth Moreland, Chris R. Johnson, Scott Klasky, Norbert Podhorszki, and Tushar M. Athawale. FunM2C: A Filter for Uncertainty Visualization of Multivariate Data on Multi-Core Devices, In Proceedings IEEE Workshop on Uncertainty Visualization, pages 43–47, October 2024. doi:10.1109/UncertaintyVisualization63963.2024.00010.

  11. Kenneth Moreland. The VTK-m User’s Guide, Oak Ridge National Laboratory, Technical Report ORNL/TM-2024/3443, 2024. https://gitlab.kitware.com/vtk/vtk-m-user-guide/-/wikis/home.

  12. Kenneth Moreland, Tushar M. Athawale, Vicente Bolea, Mark Bolstad, Eric Brugger, Hank Childs, Axel Huebl, Li-Ta Lo, Berk Geveci, Nicole Marsaglia, Sujin Philip, David Pugmire, Silvio Rizzi, Zhe Wang, and Abhishek Yenpure. Visualization at exascale: Making it all work with VTK-m, The International Journal of High Performance Computing Applications, 38(5):508–526, 2024. doi:10.1177/10943420241270969.

  13. Mark Bolstad, Kenneth Moreland, David Pugmire, David Rogers, Li-Ta Lo, Berk Geveci, Hank Childs, and Silvio Rizzi. VTK-m: Visualization for the Exascale Era and Beyond, In ACM SIGGRAPH 2023 Talks, August 2023. doi:10.1145/3587421.3595466.

  14. Zhe Wang, Tushar M. Athawale, Kenneth Moreland, Jieyang Chen, Chris R. Johnson, and David Pugmire. FunMC2: A Filter for Uncertainty Visualization of Marching Cubes on Multi-Core Devices, In Eurographics Symposium on Parallel Graphics and Visualization (EGPGV), May 2023. doi:10.2312/pgv.20231081.

  15. Sujin Philip, Kenneth Moreland, and Robert Maynard. VTK-m Accelerated Filters in VTK and ParaView, Kitware Source, 2023. https://www.kitware.com/vtk-m-accelerated-filters-in-vtk-and-paraview/.

  16. Hamish A. Carr, Oliver Rübel, and Gunther H. Weber. Distributed Hierarchical Contour Trees, In IEEESymposium on Large Data Analysis and Visualization (LDAV), pages 1–10, October 2022. WinnerBest Paper. doi:10.1109/LDAV57265.2022.9966394.

  17. Kenneth Moreland, Robert Maynard, David Pugmire, Abhishek Yenpure, Allison Vacanti, Matthew Larsen, and Hank Childs. Minimizing Development Costs for Efficient Many-Core Visualization Using MCD3, Parallel Computing, 108(102834), December 2021. doi:10.1016/j.parco.2021.102834.

  18. Rob Farber. ECP Brings Much Needed Visualization Software to Exascale and GPU-Accelerated Systems, ECP Technical Highlights, November 2021. https://www.exascaleproject.org/highlight/ecp-brings-much-needed-visualization-software-to-exascale-and-gpu-accelerated-systems/.

  19. Hamish A Carr, Oliver R{“u}bel, Gunther H Weber, and James P Ahrens. Optimization and Augmentation for Data Parallel Contour Trees, IEEE Transactions on Visualization and Computer Graphics, 28(10):3471–3485, October 2021. doi:10.1109/TVCG.2021.3064385.

  20. Sudhanshu Sane, Chris R. Johnson, and Hank Childs. Investigating In Situ Reduction via Lagrangian Representations for Cosmology and Seismology Applications, In Computational Science – ICCS 2021, pages 436–450, June 2021. Winner: Best Paper. doi:10.1007/978-3-030-77961-0_36.

  21. Sudhanshu Sane, Abhishek Yenpure, Roxana Bujack, Matthew Larsen, Kenneth Moreland, Christoph Garth, Chris R. Johnson, and Hank Childs. Scalable In Situ Computation of Lagrangian Representations via Local Flow Maps, In Eurographics Symposium on Parallel Graphics and Visualization (EGPGV), June 2021. Winner: Best Paper. doi:10.2312/pgv.20211040.

  22. Hamish A. Carr, Gunther H. Weber, Christopher M. Sewell, Oliver Rübel, Patricia Fasel, and James P. Ahrens. Scalable Contour Tree Computation by Data Parallel Peak Pruning, IEEE Transactions on Visualization and Computer Graphics, 27(4):2437–2454, April 2021. doi:10.1109/TVCG.2019.2948616.

  23. David Pugmire, Caitlin Ross, Nicholas Thompson, James Kress, Chuck Atkins, Scott Klasky, and Berk Geveci. Fides: A General Purpose Data Model Library for Streaming Data, In ISC High Performance, pages 495–507, 2021. doi:https://doi.org/10.1007/978-3-030-90539-2_34.

  24. Samuel D. Schwartz, Hank Childs, and David Pugmire. Machine Learning-Based Autotuning for Parallel Particle Advection, In Eurographics Symposium on Parallel Graphics and Visualization (EGPGV), 2021. doi:10.2312/pgv.20211039.

  25. Petar Hristov, Gunther H. Weber, Hamish A. Carr, Oliver Rübel, and James P. Ahrens. Data Parallel Hypersweeps for in Situ Topological Analysis, In IEEESymposium on Large Data Analysis and Visualization (LDAV), pages 12–21, October 2020. doi:10.1109/LDAV51489.2020.00008.

  26. Brenton Lessley, Shaomeng Li, and Hank Childs. HashFight: A Platform-Portable Hash Table for Multi-Core and Many-Core Architectures, In Electronic Imaging, Visualization and Data Analysis, pages 376-1-376-13(13), 2020. doi:10.2352/ISSN.2470-1173.2020.1.VDA-376.

  27. Talita Perciano, Colleen Heinemann, David Camp, Brenton Lessley, and E. Wes Bethel. Shared-Memory Parallel Probabilistic Graphical Modeling Optimization: Comparison of Threads, OpenMP, and Data-Parallel Primitives, In High Performance Computing, pages 127–145, 2020. doi:10.1007/978-3-030-50743-5_7.

  28. Ko-Chih Wang, Jiayi Xu, Jonathan Woodring, and Han-Wei Shen. Statistical Super Resolution for Data Analysis and Visualization of Large Scale Cosmological Simulations, In IEEE Pacific Visualization Symposium (PacificVis), pages 303–312, April 2019. doi:10.1109/PacificVis.2019.00043.

  29. Abhishek Yenpure, Hank Childs, and Kenneth Moreland. Efficient Point Merging Using Data Parallel Techniques, In Eurographics Symposium on Parallel Graphics and Visualization (EGPGV), 2019. http://www.kennethmoreland.com/topology-threading#EGPGV2019. doi:10.2312/pgv.20191112.

  30. Brenton Lessley, Talita Perciano, Colleen Heinemann, David Camp, Hank Childs, and E. Wes Bethel. DPP-PMRF: Rethinking Optimization for a Probabilistic Graphical Model Using Data-Parallel Primitives, In Proceedings of IEEE Symposium on Large Data Analysis and Visualization (LDAV), pages 34–44, 2018. doi:10.1109/LDAV.2018.8739239.

  31. David Pugmire, Abhishek Yenpure, Mark Kim, James Kress, Robert Maynard, Hank Childs, and Bernd Hentschel. Performance-Portable Particle Advection with VTK-m, In Eurographics Symposium on Parallel Graphics and Visualization (EGPGV), pages 45–55, 2018. http://cdux.cs.uoregon.edu/pubs/PugmireEGPGV.pdf. doi:10.2312/pgv.20181094.

  32. Brenton Lessley, Kenneth Moreland, Matthew Larsen, and Hank Childs. Techniques for Data-Parallel Searching for Duplicate Elements, In IEEE Symposium on Large Data Analysis and Visualization (LDAV), 2017. doi:10.1109/LDAV.2017.8231845.

  33. Brenton Lessley, Talita Perciano, Manish Mathai, Hank Childs, and E. Wes Bethel. Maximal Clique Enumeration with Data-Parallel Primitives, In IEEE Symposium on Large Data Analysis and Visualization (LDAV), 2017. http://cdux.cs.uoregon.edu/pubs/LessleyLDAV2.pdf. doi:10.1109/LDAV.2017.8231847.

  34. Shaomeng Li, Nicole Marsaglia, Vincent Chen, Christopher Sewell, John Clyne, and Hank Childs. Achieving Portable Performance For Wavelet Compression Using Data Parallel Primitives, In Proceedings of EuroGraphics Symposium on Parallel Graphics and Visualization (EGPGV), pages 73–81, 2017. http://cdux.cs.uoregon.edu/pubs/LiEGPGV.pdf. doi:10.2312/pgv.20171095.

  35. Hamish Carr, Gunther Weber, Christopher Sewell, and James Ahrens. Parallel Peak Pruning for Scalable SMP Contour Tree Computation, In Proceedings of the IEEE Symposium on Large Data Analysis and Visualization (LDAV), 2016. doi:10.1109/LDAV.2016.7874312.

  36. Brenton Lessley, Roba Binyahib, Robert Maynard, and Hank Childs. External Facelist Calculation with Data-Parallel Primitives, In Eurographics Symposium on Parallel Graphics and Visualization (EGPGV), 2016. http://cdux.cs.uoregon.edu/pubs/LessleyEGPGV.pdf. doi:10.2312/pgv.20161178.

  37. Kenneth Moreland, Christopher Sewell, William Usher, Li-Ta Lo, Jeremy Meredith, David Pugmire, James Kress, Hendrik Schroots, Kwan-Liu Ma, Hank Childs, Matthew Larsen, Chun-Ming Chen, Robert Maynard, and Berk Geveci. VTK-m: Accelerating the Visualization Toolkit for Massively Threaded Architectures, IEEE Computer Graphics and Applications, 36(3):48–58, 2016. http://dx.doi.org/10.1109/MCG.2016.48. doi:10.1109/MCG.2016.48.

  38. Matthew Larsen, Stephanie Labasan, Paul Navr'{a}til, Jeremy Meredith, and Hank Childs. Volume Rendering Via Data-Parallel Primitives, In Eurographics Symposium on Parallel Graphics and Visualization, 2015. http://cdux.cs.uoregon.edu/pubs/LarsenEGPGV.pdf. doi:10.2312/pgv.20151155.

  39. Matthew Larsen, Jeremy S. Meredith, Paul A. Navratil, and Hank Childs. Ray Tracing Within a Data Parallel Framework, In IEEE Pacific Visualization Symposium (PacificVis), pages 279–286, 2015. http://dx.doi.org/10.1109/PACIFICVIS.2015.7156388. doi:10.1109/PACIFICVIS.2015.7156388.

  40. Kenneth Moreland, Matthew Larsen, and Hank Childs. Visualization for Exascale: Portable Performance is Critical, Supercomputing Frontiers and Innovations, 2(3), 2015. http://dx.doi.org/10.14529/jsfi150306. doi:10.14529/jsfi150306.

  41. Hendrik A. Schroots and Kwan-Liu Ma. Volume rendering with data parallel visualization frameworks for emerging high performance computing architectures, In SIGGRAPH Asia Visualization in High Performance Computing, pages 3:1–3:4, 2015. doi:10.1145/2818517.2818546.

  42. Christopher Sewell, Li-ta Lo, Katrin Heitmann, Salman Habib, and James Ahrens. Utilizing many-core accelerators for halo and center finding within a cosmology simulation, In IEEE 5th Symposium on Large Data Analysis and Visualization (LDAV), 2015. doi:10.1109/LDAV.2015.7348076.

  43. Robert Maynard, Kenneth Moreland, Utkarsh Ayachit, Berk Geveci, and Kwan-Liu Ma. Optimizing Threshold for Extreme Scale Analysis, In Visualization and Data Analysis 2013, Proceedings of SPIE-IS&T Electronic Imaging, 2013. doi:10.1117/12.2007320.