the paraview guide a parallel visualization application

In High Performance Visualization: Enabling Extreme-Scale Scientific Insight, pages 357–372. VisIt: An End-User Tool For Visualizing and Analyzing Very Large Data. Wes Bethel, David Camp, Oliver Ru ̈bel, Marc Durant, Jean M. Weber, Hari Krishnan, Thomas Fogal, Allen Sanderson, Christoph Garth, E. Hank Childs, Eric Brugger, Brad Whitlock, Jeremy Meredith, Sean Ahern, David Pugmire, Kathleen Biagas, Mark Miller, Cyrus Harrison, Gunther H. Vector Models for Data-Parallel Computing. GPU Computing Gems, Jade Edition, chapter Thrust: A Productivity-Oriented Library for CUDA, pages 359–371. High-productivity CUDA development with the thrust template library. The ParaView Guide: A Parallel Visualization Application. program-documents/docs/Exascale-ASCR-Analysis.pdf. Report from the DOE ASCR 2011 Workshop on Exascale Data Management, Analy- sis, and Visualization, February 2011. Sean Ahern, Arie Shoshani, Kwan-Liu Ma, et al. We can achieve performance portability by optimizing this small set of data parallel primitives whose tuning conveys to the conglomerates.

To address these visualization needs across multiple platforms, we are embracing the use of data parallel primitives that encapsulate highly efficient parallel algorithms that can be used as building blocks for conglomerate visualization algorithms. Of the many fundamental changes we are seeing in HPC systems, one of the most profound is a reliance on new processor types optimized for execution bandwidth over latency hiding. Multiple vendors create such accelerator processors, each with significantly different features and performance characteristics. Researchers face a daunting task to provide scientific visualization capabilities for exascale computing.

Sandia National Laboratories, Albuquerque

The paraview guide a parallel visualization application