Scientific Visualization with Blender on HPC Systems

Transform complex scientific data into stunning, publication-quality images and animations. This course teaches efficient scientific visualization workflows using Blender on HPC systems — from importing multidimensional data to rendering photorealistic images and animations on multi-node clusters.

Participants learn to navigate Blender, import scientific data formats (point clouds, volumetric datasets, isosurfaces, molecular structures), and apply professional lighting, materials, and editing to produce visually compelling scientific imagery. The advanced module covers Python scripting (bpy API), Geometry Nodes for procedural generation, and advanced shading — culminating in an independent project using your own research data.

The course also introduces HPC-specific workflows: headless rendering via command-line, distributed Cycles rendering on GPU clusters, and integration with ParaView, VisIt, and VTK. Gain hands-on experience scaling visualization pipelines from desktop to production HPCsystems.

By the end, you'll build and execute complete scientific visualization pipelines, from data import and mesh processing to rendering and animation. Finally we show how to leverage modern HPC infrastructure to render high resolution, high quality imagery andmovies.

Agenda & Content

For a detailed timetable and additional information, please see Agenda & Content in the left menu.

Target audience, eligibility & prices

Everyone is welcome who wants to get an introduction to scientific vizualization with Blender on HPC systems.

This course is open and free of charge for all participants from academia, industry, and public administration from EU and/or EuroHPC JU member countries.

Entry level & prerequisites

Beginner – no prior experience visualization or Blender is necessary.

Course format

This course will be delivered as a LIVE ONLINE COURSE (using Zoom).

Hands-on labs

All participants will get a temporary user account on one of the ASC systems to do the hands-on labs.

You will use your own laptop or workstation to connect conveniently from your browser to the ASC Jupyterhub and do the hands-on exercises on a suitable CPU or GPU partition of the ASC.

Accepted participants will be contacted a few days before the course and asked to do a short pre-assignment that has to be completed before the course starts.

Lecturer

Thomas Haschka (Campus IT / HPC, TU Wien)    
Dr. Thomas Haschka is an Austrian biophysicist and computational scientist specializing in molecular biophysics, high-performance computing, machine learning and Artificial Intelligence. He currently works as an AI Specialist in the dataLAB of the High-Performance Computing Unit at Campus IT, TU Wien, supporting advanced research infrastructure and data-driven innovation. With a PhD from Université de Reims Champagne-Ardenne (highest distinction), he has held research positions at institutions such as the Pasteur Institute, Paris Brain Institute, and the American University of Beirut. His work spans molecular dynamics, epidemiological modeling, genomics, and AI evaluation methods, supported by strong expertise in GPU programming and cloud technologies. He combines academic research excellence with real-world industrial consulting experience.

Language

English

Date, time, and location

01.–02.12.2026, 09:00 – 13:00 (CET), LIVE ONLINE COURSE (Zoom)

Registration

Registration is required, the registration form can be found on top of this page in the menu on the left.

Please register with your official institutional email address to prove your affiliation.

You will get an automatic confirmation by email (subject starting with "[Indico] Registration"), please check your Spam/Junk folders.

Following your successful registration, you will receive further information a few days before the course.

Please do not hesitate to contact us at training@asc.ac.at if you have any questions.

Waitinglist

After the number of registrations has reached its maximum or the registration form has been closed, you may want to send us an email (training@asc.ac.at) stating that you are interested to be put on the waiting list (vacancies may occur due to cancelations, etc.).

To be able to do the hands-on labs on the ASC systems please provide your full international mobile-phone number for the two-factor authentication required to login to the ASC systems.

Modification, withdrawal & no-show policy

Your registration is binding. Please only register for the course if you are really going to attend.

You can update your registration data or withdraw your registration anytime before the registration form has been closed via the link "Manage my registration" which you can find at the bottom of your automatic email confirmation (subject starting with "[Indico] Registration").

Alternatively, or after the registration form has been closed, please inform us about your cancelation or any change in your registration data (especially your mobile-phone number) via email (training@asc.ac.at).

No-show policy: If you do not cancel and do not show up at the course you will be blacklisted and excluded from future training events.

Organizers

This course is organized by Austrian Scientific Computing ASC (aka ASC Research Center, TU Wien).

Acknowledgements

This course is partially funded by the EuroCC 3 project.

EuroCC 3 has received funding from the European High-Performance Computing Joint Undertaking (JU) under Grant Agreement No. 101306701. The JU receives support from the European Union‘s Digital Europe Programme and Germany, Albania, Austria, Belgium, Bosnia and Herzegovina, Bulgaria, Croatia, Cyprus, Czechia, Denmark, Estonia, Finland, France, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, Montenegro, the Netherlands, North Macedonia, Norway, Poland, Portugal, Romania, Serbia, Slovakia, Slovenia, Spain, Sweden, Türkiye, and Kosovo.

Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or EuroHPC Joint Undertaking. Neither the European Union nor the EuroHPC Joint Undertaking can be held responsible for them.

National co-funding for Austria was granted by Austrian Scientific Computing (ASC).