The course will focus on visualization of scientific data that can come from simulations of different physical phenomena (e.g. fluid dynamics, structural analysis, etc.). To create visually pleasing outputs of such data a path tracing rendering method will be used. All of the course aspects will be covered within the popular 3D creation suite Blender. We will work with the 2.8 version and introduce two of our plug-ins we have developed. The first one, called Covise Nodes is used to extend Blender capabilities to process scientific data. The second add-on is called Bheappe and it integrates cluster rendering in Blender. Within the course we will demonstrate some of the basics of Blender, followed by a data visualization example, and we will finish the course with rendering of a created scene on a supercomputing cluster.
This course, postponed from April 2020, due to the COVID-19 pandemic, is an enriched rerun of a successful training from 2019.
NOTE: The organization of the course will be adapted to the current COVID-19 regulations and participants must comply with them. In case of the forced reduction of the number of participants, earlier registrations will be given priority.
Purpose of the course (benefits for the attendees)
Attendees will learn how to visualize different simulation data in Blender and how to provide visually pleasing outputs with help of a cluster.
About the tutor(s)
Petr Strakoš obtained his Ph.D. from CTU (the Czech Technical University in Prague) in Mechanical Engineering. Now he is a member of the Infrastructure Research Lab and the VaVR (Visualization and Virtual Reality) group, where he focuses on research in the area of visualization, image processing, and efficient utilization of these topics on a cluster. He also cooperates with partners from industry and other institutions in applied research.
Milan Jaroš is a researcher in the Infrastructure Research Lab at IT4Innovations. He has nine years of experience in professional programming (C++, C#, Java, etc.). He has developed several pieces of commercial software (including mobile applications). In recent years he has been focusing on research in the area of HPC computing (including support of GPU and Intel Xeon Phi coprocessor), processing of medical images, and visualizations of engineering data (virtual reality, rendering, post-processing of CFD calculation, etc.). He is a co-developer of plugins for multiple pieces of software (Blender, COVISE/OpenCOVER, Unity, etc.).
Alena Ješko is a researcher in the Infrastructure Research Lab at IT4Innovations. She has worked on mesh transformation topics for cranial orthosis design and photogrammetry for treating orbital fractures. She has recently started to work on AI and Machine Learning in Image Processing.
This event was partially supported by The Ministry of Education, Youth and Sports from the Large Infrastructures for Research, Experimental Development and Innovations project "e-Infrastruktura CZ – LM2018140“ and partially by the PRACE-6IP project - the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 823767. This work was also partially supported by the SGC grant No. SP2020/21 "Infrastructure research and development of HPC libraries and tools II", VŠB - Technical University of Ostrava, Czech Republic.