MegaMol is a cross-platform visualization prototyping framework that was started at the Visualization Research Center of the University of Stuttgart in context of the Collaborative Research Center (SFB) 716. It also includes numerous contributions from the Chair of Computer Graphics and Visualisation of TU Dresden.
MegaMol is the preferred visualization tool of the developers of the molecular dynamics (MD) simulation program ls1 mardyn. It can easily be configured to write native MegaMol file formats.
MegaMol development is and was partially supported by the German Research Foundation (DFG) as part of Collaborative Research Center (SFB) 716, by the Intel® Parallel Computing Center program, the ScaDS Dresden/Leipzig Competence Center for Scalable Data Services and Solutions, the ESF program Visual and Interactive Cyber-physical Systems Control and Integration (VICCI), and by BW Stiftung as part of the project Digital Human.
VISUS is part of the VR Expo on the Vaihingen Campus of Uni Stuttgart. You can still drop by and see our VR/AR demos until tomorrow at noon. We have HoloLens demos, VR demos, and, of course, MegaMol running on our Powerwall. You can see the premiere of MegaMol rendering on Stampede2 at TACC with […]
We are proud to announce MegaMol was part of the Intel Select Solution for Professional Visualization Launch! We had a demo running at the Intel booth on the ISC expo floor. The interactive visualization of 34 billion particles was streamed from render nodes located in Oregon, where another Select Solution machine was prepared to balance […]
We had a live MegaMol demo running the integrated OSPRay at the Intel booth of Supercomputing 2017. It showed a fluid simulation by our project partners Matthias Heinen and Prof. Jadran Vrabec from the Chair of Thermodynamics and Energy Technology at the University of Paderborn.
VISUS has recently been funded as the first Intel® PCC for Visualization in Europe! With this funding, we plan to integrate Software-Defined Visualization into MegaMol. That way, it will work on a wider range of hardware and easily scale to larger data set sizes. Combined with some other changes, the upcoming 1.3 release already contains […]