Insight into your datasets
Visualisation is an important aid for gaining insight into your sets of research data. In many cases, numerical data analysis provides too little insight. Visualisation give you a good first impression of the results, allowing you to study interesting data trends, check the accuracy of results and present the results in an understandable way.
Parallel data analysis and visualisation
More and more researchers are using parallel HPC systems, such as the Cartesius supercomputer. These systems often generate extremely large datasets, requiring researchers to have parallel systems for data analysis and visualisation. SURF is responding to this demand.
SURF offers you the opportunity to perform remote visualisation by means of Cartesius and HPC Cloud. Both use GPUs for high-performance visualisation. Therefore when performing calculations on Cartesius, you can easily visualise your data.
Visualisation allows you to use a large number of nodes and GPUs, which in turn make it possible to visualise large datasets in various scales. The resulting visualisations are much larger than what is possible on a PC or laptop. These visualisations can be viewed on your own desktop system. This requires a modest amount of bandwidth – a typical office network (100+Mbit/s) is usually sufficient.
Users can always count on us for support. SURF provides support for use of the visualisation cluster and the installed software. For example, we can help you with distributed visualisations of large datasets, for which we use visualisation software such as ParaView and VisIt. You can consult online manuals for suggestions regarding better performance, and more.
You can contact our helpdesk by telephone or email, but we can also assist you in person. If you have any questions, or want to report a problem, please send an email to firstname.lastname@example.org or phone +31-208001400. The helpdesk is available during office hours (9:00–17:00).
If you would like specific advice about developing and integrating visualisation methods and applications or about large-scale parallel visualisations, please get in touch with our consultancy service.