Referencing ParaView

If you are working with ParaView and need to formally reference it, please use one of the following:

  • Ahrens, James, Geveci, Berk, Law, Charles, ParaView: An End-User Tool for Large Data Visualization, Visualization Handbook, Elsevier, 2005, ISBN-13: 978-0123875822
  • Ayachit, Utkarsh, The ParaView Guide: A Parallel Visualization Application, Kitware, 2015, ISBN 978-1930934306

Recent ParaView Publications

As an active open-source project, ParaView is well represented in recent publications. The list below represents a sample of recent publications.

  • Nov-2014. James Ahrens, Sébastien Jourdain, Patrick O’Leary, John Patchett, David H Rogers, Mark Petersen. An image-based approach to extreme scale in situ visualization and analysis, Proceedings of the International Conference for High Performance Computing.
  • Oct-2014. Woodring J., Ahrens J., Tautges T., Peterka T., Vishwanath V., Geveci B., On-demand unstructured mesh translation for reducing memory pressure during in situ analysis, UltraVis ’13 Proceedings of the 8th International Workshop on Ultrascale Visualization.
  • Oct-2014. Karimabadi H., Loring B., O’Leary P., Majumdar A., Tatineni M., Geveci B., In-situ visualization for global hybrid simulations, Proceedings of the Conference on Extreme Science and Engineering Discovery Environment: Gateway to Discovery.
  • June-2014. Karimabadi H., Roytershteyn V., Vu H.X., Omelchenko Y.A., Scudder J., Daughton W., Dimmock A., Nykyri K., Wan M., Sibeck D., Tatineni M., Majumdar A., Loring B., Geveci B., The link between shocks, turbulence, and magnetic reconnection in collisionless plasmas, Physics of Plasmas, AIP Publishing.
  • Dec-2013, Nouanesengsy B., Patchett J., Ahrens J., Bauer A., Chaudhary A., Miller R., Geveci B., M Shipman G., N Williams D., A model for optimizing file access patterns using spatio-temporal parallelism, Proceedings of the 8th International Workshop on Ultrascale Visualization.
  • Sep-2013. DeMarle D., Geveci B., Ahrens J., Woodring J., Streaming and Out-of-Core methods, High Performance Visualization: Enabling Extreme Scale Scientific Insight, CRC Press