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LUNARC Townhall meeting

Are your computing needs growing larger than your computer? You need help improving your scientific workflows? Curious about what LUNARC can offer for you or your research group? Do you have questions regarding the use of LUNARC services? Are you interested in taking part in the development of future LUNARC services? Are there other services you think LUNARC should provide?

If your answer is yes to any of the above questions, please join us on the 17/2 10.00-12.30 for the LUNARC Townhall meeting.

It is very important to us to obtain your input on how you want LUNARC to develop in the future. During the meeting new and experienced LUNARC users will showcase how they use LUNARC’s services. After the presentations we will open several breakout rooms where you can provide input and discuss key aspects of LUNARC’s future infrastructure and services.

10:0010:05 Welcome 


Presentation slides

User presentations
10:2010:30AstronomyExploring the mysteries of the universe with LunarcAlexey Bobrick
   Lunarc has been a significant source of astrophysical discovery in Lund. As big and diverse as the Universe, so are the problems we tackle. I will review some of our recent research highlights: the formation of galaxies, the exciting events happening near and far from their central supermassive black holes, the formation of planets and mergers of compact stars, showcasing how the versatility of the Lunarc cluster has been vital for us.

Presentation slides

10:3010:40Theoretical Chemistry The science we do with LUNARC.Valera Veryazov

The Division of Theoretical Chemistry was one of the founders of LUNARC and since then we have had a long and successful relationship. In this presentation we show the variety of scientific achievements, which are only possible because of computational resources and the support from LUNARC. We also present SWOT analysis for the development of our future.

Presentation slides

10:4010:50MedicinThe Faculty of Medicine and LUNARC Kajsa M Paulsson

Researchers at the Faculty of Medicine generate vast amount of data from e.g. imaging, genomics and proteomics, and also process extensive data generated in health care settings. In the imaging field, significant challenges and opportunities exist not least regarding data from synchrotron light, free electron laser light and neutron facilities. The processing and handling of both complex and large data sets is a major bottle-neck for many researchers and significantly slows down the projects. Solutions to access a variety of software, secure data storage as well as powerful CPU and GPU hardware are urgently required by many researchers, e.g. for omics data analysis, 2, 3 and 4D data visualisations and machine learning. Hosted at the faculty of Medicine there are a number of initiatives including Lund University Bioinformatics Infrastructure (LUBI-LSGA) and Correlative Image Processing and Analysis (CIPA) that together with LUNARC offer the opportunity to request help and acquire the skills needed  and to partake in a community committed to enable researchers to make the most use of their acquired data.

Presentation slides 

10:5011:00ArcheologyUsing High-Performance Computing Resources for the Record and Analysis of Cultural Heritage SitesNicoló Dell'Unto, Giacomo Landeschi and Paola Derudas

This talk focuses on the three-dimensional acquisition workflows of large cultural heritage sites where High-Performance Computing resources were employed.
During the presentation, several case studies will be presented and discussed.

Presentation slides

11:0011:10MedicinAnalysing biomedical image and text data with machine learning and CellProfilerSonia Aits

Processes in the cell are regulated by a chain of interacting proteins and molecules which form biological signalling pathways. In our research, we try to identify the cellular pathways which regulate cell death and related processes, as well as drugs that can correct disease-causing disruptions in these pathways. We also try to understand the effect of Sars-CoV-2 on the organism as a whole and on cellular signalling pathways, and find drugs that can counteract its effect.

For this purpose, we are developing machine learning methods for mining biomedical literature and electronic health records. In addition, we are using both machine learning and CellProfiler software for analysing microscopy image data set on a small and very large scale.    

Presentation slides

11:1011:20MAX IVMAX IV and LUNARCZdenek Matej

MAX IV Laboratory is a Swedish national research infrastructure providing scientists with X-rays for their research. Researchers from diverse scientific domains including life-sciences, chemistry, material science or fundamental physics can be generating very large datasets during their experiments in MAX IV beamlines. Large data volumes are having high resource requirements, including beside storage capacity also memory, storage I/O and compute capacity. This can often be related to losing a momentum in data analysis when the experiment is finished. Other way around a quick feedback is expected and valued. Data analysis tools need to have user-friendly and interactive interface easy to understand for non-expert users. In the last years MAX IV was working together with LUNARC on making MAX IV data easily accessible at AURORA and the same is true for many specific synchrotron data analysis software. Current activities and some applications, in particular for macromolecular crystallography and x-ray imaging, will be presented.

Presentation slides

Breakout sessions
11:2012:10 I am planning to use LUNARC. How can I benefit from LUNARC resources and knowledge? 
   I have recently started to use LUNARC. How can LUNARC improve the experience of its resources and services? 
   I am long-standing LUNARC user. How can LUNARC provide better resources and services in the future? 
12:1012:30 Summary QA 

A Zoom-link will be shared with the registered participants prior to the meeting.



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