[HYBRID] SPACE: High-Performance Computing (HPC) Visualization

This workshop is organised by the SPACE CoE in collaboration with NCC Czechia and CASTIEL 2.

Annotation

The workshop on High-Performance Computing (HPC) Visualisation will focus on cutting-edge tools and techniques for handling the vast datasets produced by large-scale simulations and observational surveys in astrophysics and cosmology.

The growing complexity of astrophysical and cosmological data—whether from massive simulations or large-scale observational campaigns—requires powerful visualisation tools to extract scientific insights. However, implementing these tools efficiently on diverse HPC platforms presents challenges such as hardware and software compatibility, scalability, and resource optimisation.

This workshop will explore strategies to overcome these challenges and highlight recent advances in high-performance visualisation, including:

• Distributed visualisation in heterogeneous architectures
• Parallel cinematic volume visualisation
• In-situ visualisation
• Visualisation methods for machine learning-assisted analysis

While the primary focus is astrophysics and cosmology, these techniques have broad applications across other scientific domains dealing with large and complex datasets. We encourage participation from researchers and developers interested in state-of-the-art visualisation methods.

Language

English

Tutors

Giuseppe Tudisco (INAF) holds a Master's degree in Computer Science (Network and Security Systems) from the University of Catania (2020). He is a technologist at the Italian National Institute for Astrophysics (INAF), based at the Astrophysical Observatory of Catania. His expertise spans scientific visualisation, data analytics, and distributed computing, leading the development of VisIVO tools. He has contributed to several international projects, including H2020 NEANIAS, ERC ECOGAL, SKA, and the Italian National Centre for HPC, Big Data, and Quantum Computing. Since 2022, he has been actively involved in the development of SKA Regional Centres, serving as Scrum Master for two Agile teams: Orange, focused on visualisation prototypes for SKA, and Azure, dedicated to developing the Italian Regional Centre (ITSRC).

Nicola Tuccari (INAF) is a PhD student in Computer Science at the University of Catania and INAF. He also holds a master's degree in Computer Science. His main research topics are data visualisation and parallel computing. He is currently involved in the Italian National Center for HPC, Big Data, and Quantum Computing and actively collaborates with the SPACE CoE project.

Yolanda Becerra (BSC) is a full-time associate professor at the Computer Architecture Department of the Universitat Politécnica de Catalunya (UPC) and an associate researcher at the Barcelona Supercomputing Center (BSC). She holds a PhD in Computer Science since 2006 from the UPC. In 2007, she joined the BSC, where she is currently leading the Data-Driven Scientific Computing research activity in the Workflows and Distributed Computing group. Her research interests are focused on designing data management policies to improve the performance of scientific applications and on designing models and interfaces that facilitate scientists' analysis of their data.

Enric Sosa (BSC) is a junior researcher engineer at the Barcelona Supercomputing Center. In 2020, he received his BSC in Informatics Engineering degree from the Universitat Politécnica de Catalunya (UPC). He has been part of the Data-Driven Scientific Computing group since 2018. His research focuses on hardware performance and data models for storage systems.

Sebastian Trujillo Gomez (HITS) is a theoretical astrophysicist who has dedicated his career to studying the formation of large-scale structure and galaxies in a cosmological context and the nature of dark matter. His research currently focuses on using Deep Learning to enable scientific discovery from the largest simulated and observational datasets, and in particular, developing methods to robustly confront cosmological and galaxy formation models with observational data. He is currently a research scientist in the Astroinformatics group at the Heidelberg Institute for Theoretical Studies in Germany.

Bernd Doser (HITS) is currently employed as a senior scientific software engineer at the Heidelberg Institute for Theoretical Studies. His responsibilities include implementing modern software engineering practices and maintaining various open-source packages across different scientific disciplines. Bernd holds a Ph.D. in computational chemistry and is an expert in high-performance computing, numerical algorithms, and machine learning.

Marta Barroso Isidoro (BSC) has more than four years of experience applying Machine Learning and Deep Learning to diverse research projects, including CIBERES-UCI-COVID and KnowlEdge, where she served as Principal Investigator. She is also skilled in project management, overseeing planning, resource allocation, engineering tasks, and reporting with precision and clarity.

Pablo Agustin Martin Torres (BSC) works at the intersection between AI and Stochastic Geometry, with more than two years of experience as an AI researcher working on visual-language models training and evaluation. Other research interests include the theoretical and practical foundations of Multimodal Generative AI and Mechanistic Interpretability.

Guillermo Marin (BSC) is the lead of the Scientific Visualization and Storytelling research line at the Visualization Group of the Barcelona Supercomputing Center. His interests are in cinematic data visualisation, data conversion pipelines, and high-performance visualisation. He has also been a lecturer and trainer in several workshops, Graduate, and master's programs over the years. He is currently an Associate Professor of Data Visualization at the Universitat Autonoma de Barcelona.

Petr Strakoš (IT4Innovations) is a senior researcher and team leader in the Visualization and Virtual Reality group at IT4Innovations, VSB-TUO, specialising in high-performance computing, data visualisation, and image processing. With a Ph.D. in mechanical engineering from the Czech Technical University in Prague, he has contributed to numerous research projects in image processing, biomedical imaging, and simulations with HPC.

Milan Jaroš (IT4Innovations) is a computational scientist specialising in computer graphics and visualisation. He received his Ph.D. from VŠB —Technical University of Ostrava. As a researcher at IT4Innovations, he focuses on high-performance computing, GPU acceleration, and virtual reality, contributing to cutting-edge projects in image processing and simulations with HPC.

Acknowledgements

This work was supported by the SPACE project under grant agreement No 101093441. The project is supported by the European High-Performance Computing Joint Undertaking and its members (including top-up funding by the Ministry of Education of the Czech Republic ID: MC2304).

This project has received funding from the European High-Performance Computing Joint Undertaking (JU) under grant agreement No 101101903. The JU receives support from the Digital Europe Programme and Germany, Bulgaria, Austria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, Greece, Hungary, Ireland, Italy, Lithuania, Latvia, Poland, Portugal, Romania, Slovenia, Spain, Sweden, France, Netherlands, Belgium, Luxembourg, Slovakia, Norway, Türkiye, Republic of North Macedonia, Iceland, Montenegro, Serbia. This project has received funding from the Ministry of Education, Youth and Sports of the Czech Republic.

This course was supported by the Ministry of Education, Youth and Sports of the Czech Republic through the e-INFRA CZ (ID:90254).