Scientific Discovery via Visualization Using Accelerated Computing Scientific

Scientific Discovery via Visualization Using Accelerated Computing Scientific Achievement VTK-m updates scientific visualization software to run on the accelerated processors (like GPU and Xeon Phi) driving the most powerful HPC systems. Significance and Impact If we fail to update our scientific visualization software to run efficiently on modern HPC systems, we will lose the tools required to make scientific discoveries. Research Details Sewell, et al. Proceedings of the Ultrascale Visualization Workshop, November 2012, DOI 10. 1109/SC. Companion. 2012. 36. – Initial research was fragmented into 3 separate projects. • SDAV brought the PIs together to engage and to transition to the unified software used today. – Para. View 5. 3 and Vis. It 2. 11 offer VTK-m acceleration. – Upcoming VTK 8. 0 will offer VTK-m accelerated filters. – In situ tools demonstrated on Titan with thousands of GPUS. VTK-m started by merging EAVL, Dax, and Piston being developed 12 13 14 15 Para. View using VTK-m acceleration to visualize data from a supernova simulation. Moreland, et al. IEEE Computer Graphics and Applications, Volume 36, Number 3, May/June 2016, DOI 10. 1109/MCG. 2016. 48. VTK-m Live In Situ with Catalyst/ Py. FR VTK-m In Situ with VTK-m Catalyst/ 1. 0. 0 Py. FR batch Released mode on Titan with VTK-m 5000 GPUS Added to VTK to Vis. It and Para. View 16 17