{"$schema": "https://c3voc.de/schedule/schema.json", "generator": {"name": "pretalx", "version": "2025.2.2"}, "schedule": {"url": "https://pretalx.surf.nl/acud-2025/schedule/", "version": "0.11", "base_url": "https://pretalx.surf.nl", "conference": {"acronym": "acud-2025", "title": "Advanced Computing User Day", "start": "2025-12-04", "end": "2025-12-04", "daysCount": 1, "timeslot_duration": "00:05", "time_zone_name": "Europe/Amsterdam", "colors": {"primary": "#dd11ee"}, "rooms": [{"name": "Progress", "slug": "142-progress", "guid": "cb99caa7-30df-54ef-bae3-4eae559dae24", "description": null, "capacity": null}, {"name": "Quest", "slug": "143-quest", "guid": "625ee01d-544d-5656-b15c-7ac6c725f8a8", "description": null, "capacity": null}, {"name": "Expedition", "slug": "144-expedition", "guid": "acd37fdb-6d54-5f09-be9b-492a92a8478c", "description": null, "capacity": null}, {"name": "Mission 1", "slug": "145-mission-1", "guid": "8d937413-b6f4-5967-8917-69165be5f68b", "description": null, "capacity": null}, {"name": "Mission 2", "slug": "146-mission-2", "guid": "7b8786d5-83c5-5062-a247-38f6a53d1cb4", "description": null, "capacity": null}], "tracks": [{"name": "Plenary", "slug": "146-plenary", "color": "#6852b3"}, {"name": "Generative AI and Machine Learning", "slug": "147-generative-ai-and-machine-learning", "color": "#b3842d"}, {"name": "Innovative Technologies & Services", "slug": "144-innovative-technologies-services", "color": "#f47b34"}, {"name": "Data Processing & Cloud Solutions", "slug": "143-data-processing-cloud-solutions", "color": "#7e9db4"}, {"name": "HPC for Societal and Industrial Impact", "slug": "145-hpc-for-societal-and-industrial-impact", "color": "#4f99cc"}, {"name": "High Performance Computing", "slug": "142-high-performance-computing", "color": "#ff4eff"}], "days": [{"index": 1, "date": "2025-12-04", "day_start": "2025-12-04T04:00:00+01:00", "day_end": "2025-12-05T03:59:00+01:00", "rooms": {"Progress": [{"guid": "59433f19-970d-515b-a242-ee14fb714251", "code": "AGUFK8", "id": 4442, "logo": null, "date": "2025-12-04T09:30:00+01:00", "start": "09:30", "duration": "00:15", "room": "Progress", "slug": "acud-2025-4442-opening-experience", "url": "https://pretalx.surf.nl/acud-2025/talk/AGUFK8/", "title": "Opening Experience", "subtitle": "", "track": "Plenary", "type": "Opening Experience", "language": "en", "abstract": "**A Spark to Begin**\r\nBefore we dive into the day\u2019s discoveries, we invite you to experience a moment that will awaken your senses and set the tone for what\u2019s to come. Something unexpected will unfold , a spark of creativity and wonder to open the stage and the mind.\r\n\r\nAfter this opening act, Valeriu, our day chair and a leading figure in the advanced computing community, will take the stage to officially open the Advanced Computing User Day.", "description": "Rob and Emiel will be present at our event as energisers. They will open the day, amaze us with their award-winning World Cup act, and have promised to inspire us in the area of mindset change. We hope you are ready for some unforgettable and magical moments.", "recording_license": "", "do_not_record": false, "persons": [{"code": "EGLXJZ", "name": "Rob en Emiel", "avatar": "https://pretalx.surf.nl/media/avatars/EGLXJZ_tDTD8ac.jpg", "biography": "Rob & Emiel are renowned for delivering high-impact performances at  corporate events, combining years of experience with an unmatched track record. As the most awarded magic duo in the Netherlands, they have won 14 national gold medals and uniquely claimed the prestigious Grand Prix three times. Internationally, they earned podium places at multiple World Championships and were crowned world\u2019s best mentalists in China. With performances in over 15 countries and appearances in more than 100 television episodes like Op1, HLF8, Barend & van Dorp, Jensen, Life & Cooking, De Wereld Draait Door en Pauw & Witteman. They bring professional excellence, technical perfection, and a proven wow-factor to every business stage.", "public_name": "Rob en Emiel", "guid": "91599dfd-a908-5c7c-bc1a-40afd72424fd", "url": "https://pretalx.surf.nl/acud-2025/speaker/EGLXJZ/"}, {"code": "WZQATP", "name": "Valeriu Codreanu", "avatar": "https://pretalx.surf.nl/media/avatars/WZQATP_0lulE3q.jpeg", "biography": "With more than 15 years of experience in high-performance computing, Valeriu Codreanu is a strategic leader known for combining vision with empathy and a strong commitment to advancing research infrastructure in the Netherlands and across Europe. As Head of High-Performance Computing & Visualization at SURF, he oversees the Dutch national supercomputer Snellius, manages a portfolio exceeding \u20ac20M annually, and leads a team of over 30 specialists driving innovation in advanced computing.\r\n\r\nHe plays a central role in shaping the next generation of national infrastructure, including the upcoming tender that will unify SURF\u2019s HPC, Grid, and Cloud services into a single, future-proof research platform. His influence extends across Europe through leadership positions in VSC Tier-1, LUMI, the Jules Verne exascale consortium, and the Dutch AI Factory.\r\n\r\nPassionate about people as much as technology, Valeriu Codreanu is dedicated to mentoring talent, empowering teams, and inspiring research communities to push boundaries and achieve lasting impact.", "public_name": "Valeriu Codreanu", "guid": "5522c8a3-4022-5559-a5cb-ceaee5a9594c", "url": "https://pretalx.surf.nl/acud-2025/speaker/WZQATP/"}], "links": [], "feedback_url": "https://pretalx.surf.nl/acud-2025/talk/AGUFK8/feedback/", "origin_url": "https://pretalx.surf.nl/acud-2025/talk/AGUFK8/", "attachments": []}, {"guid": "1927ded5-0117-5476-9d16-23b3d914a216", "code": "D8NASW", "id": 4441, "logo": null, "date": "2025-12-04T09:45:00+01:00", "start": "09:45", "duration": "00:50", "room": "Progress", "slug": "acud-2025-4441-keynote-maria-girone", "url": "https://pretalx.surf.nl/acud-2025/talk/D8NASW/", "title": "Keynote Maria Girone", "subtitle": "", "track": "Plenary", "type": "Keynote", "language": "en", "abstract": "Keynote by Maria Girone, Head of CERN openlab", "description": "Maria has spent her career driving innovation at the intersection of science and computing. At CERN, she has led transformative projects that bring together HPC, AI, and cloud technologies to handle the immense data challenges of the Large Hadron Collider. A leader, collaborator, and advocate for diversity in STEM, Maria continues to inspire how we think about computing for discovery.", "recording_license": "", "do_not_record": false, "persons": [{"code": "GBGPV9", "name": "Maria Girone", "avatar": "https://pretalx.surf.nl/media/avatars/GBGPV9_2rpdxrW.png", "biography": "Maria Girone is Head of CERN openlab and Principal Applied Scientist at CERN\u2019s IT department. She has been at the forefront of scientific computing for over two decades, driving how advanced computing enables the groundbreaking research carried out at the Large Hadron Collider (LHC).\r\n\r\nAt CERN, Maria has led efforts to integrate High-Performance Computing (HPC), cloud, AI, and new data technologies into the workflows of one of the world\u2019s most data-intensive scientific experiments. She played a central role in the development and operation of the Worldwide LHC Computing Grid (WLCG). WLCG is the largest distributed computing infrastructure ever built for science, connecting hundreds of data centers worldwide to process petabytes of data from particle collisions.\r\n\r\nAs former Chief Technology Officer of CERN openlab (2016\u20132023) and now its Head, Maria has defined international R&D strategies and built strong collaborations with industry and academia to push the boundaries of computing architectures. Her work not only supports the current experiments but also prepares for the High-Luminosity LHC, which will demand unprecedented computing capacity.\r\n\r\nA strong advocate for diversity in STEM, Maria also co-founded IDEAS4HPC, the Swiss chapter of Women in HPC.", "public_name": "Maria Girone", "guid": "5ef26d55-13ec-5bab-bd96-171acdc5faba", "url": "https://pretalx.surf.nl/acud-2025/speaker/GBGPV9/"}], "links": [], "feedback_url": "https://pretalx.surf.nl/acud-2025/talk/D8NASW/feedback/", "origin_url": "https://pretalx.surf.nl/acud-2025/talk/D8NASW/", "attachments": []}, {"guid": "70b6de1a-75eb-57e4-b98e-02d977e521ba", "code": "UCP9QG", "id": 4408, "logo": null, "date": "2025-12-04T11:00:00+01:00", "start": "11:00", "duration": "00:25", "room": "Progress", "slug": "acud-2025-4408-introducing-weathergenerator", "url": "https://pretalx.surf.nl/acud-2025/talk/UCP9QG/", "title": "Introducing WeatherGenerator", "subtitle": "", "track": "Generative AI and Machine Learning", "type": "Short presentation with Q&A", "language": "en", "abstract": "Artificial intelligence has been transformative for earth and environmental sciences: nowadays this technique is a common instrument scientists\u2019 toolbox. In the domain of meteorology, machine learning often displays superior accuracy compared to traditional computational methods. Even in weather prediction, where complex numerical PDE-solving codes have seen decades of development, graph neural networks and transformer architectures have proven to produce more skillful forecast at a fraction of the computational cost. Inspired by the recent developments in generative modeling of textual data through large language models, several research groups have made efforts to design a foundation model for weather and climate, one that allows fine-tuning for specific objectives and benefits from a pre-trained rich latent space. The WeatherGenerator EU  project aims to develop the leading European AI foundation model of the atmosphere. This model will be pre-trained with petabytes of multi-modal data (reanalyses, station observations, satellite products,\u2026) on Europe\u2019s first exascale-class supercomputers, ultimately keeping Europe\u2019s global forecast capabilities at the forefront as we enter an era of democratized data-driven weather prediction.", "description": "In recent years, artificial intelligence has grown to be a ubiquitous tool in earth and environmental sciences. In meteorology and climate sciences, neural networks have shown to be  the superior strategy for a multitude of data-driven tasks such as bias correction, down-scaling and even now-casting. Lately, also weather prediction and data assimilation - traditionally the domain of state-of-the-art large numerical HPC codes - have shown substantial improvements by using graph neural networks or transformer architectures. As a result, the current best weather forecasts are obtained with models such as Google\u2019s graphcast and the ECMWF\u2019s AIFS, both trained on the global reanalysis dataset ERA5. As a bonus, the inference rollout requires just a fraction of the computational cost of a traditional forecast.\r\n\r\nAlthough machine learning outperforms traditional methods in these specific tasks, the question remains whether a unified core model, equipped with a rich latent space, opens the pathway towards improved predictive skill and increased flexibility. Several initiatives to build such a foundation model of the atmosphere have emerged and shown promising results. Within the EU project WeatherGenerator, we aim to construct a large, high-resolution foundation model for weather prediction and atmospheric climate modeling. We aim to combine a very large volume of reanalysis products, observational data and climate model output into a multi-channel transformer architecture that can easily be fine-tuned to execute common weather modeling and prediction tasks. The pre-training will be a technical feat that has to be executed on Europe\u2019s exascale compute infrastructure. To substantiate the claim of being a foundation model, the project hosts many stakeholders that will re-implement existing ML applications with the WeatherGenerator model.\r\n\r\nIn this talk I will motivate this ambitious endeavour and outline the innovative ideas and techniques behind WeatherGenerator. I will briefly discuss some of the future applications and explain how the Netherlands eScience Center plans to bring this technology to potential stakeholders such as the European research community, public institutions and industry.", "recording_license": "", "do_not_record": false, "persons": [{"code": "PMC8KE", "name": "Gijs van den Oord", "avatar": "https://pretalx.surf.nl/media/avatars/PMC8KE_wpw7i8H.jpg", "biography": "Gijs studied Theoretical Physics and Mathematics at Utrecht University. Thereafter, he did a PhD in Particle Physics at the Radboud University Nijmegen and Nikhef. Subsequently, he worked as a consultant in scientific software development on environmental models and hydrodynamical solvers at Deltares. Gijs joined the Netherlands eScience Center in 2016 and has primarily been involved in projects in weather, climate and hydrology. Gijs became head of the natural sciences & engineering section in 2024.a", "public_name": "Gijs van den Oord", "guid": "5ed7ba62-0742-5e33-9f08-63e8842826db", "url": "https://pretalx.surf.nl/acud-2025/speaker/PMC8KE/"}], "links": [], "feedback_url": "https://pretalx.surf.nl/acud-2025/talk/UCP9QG/feedback/", "origin_url": "https://pretalx.surf.nl/acud-2025/talk/UCP9QG/", "attachments": []}, {"guid": "122472ba-cc45-5385-82a8-ce4a5c5a7770", "code": "A8QYRM", "id": 4480, "logo": null, "date": "2025-12-04T11:30:00+01:00", "start": "11:30", "duration": "00:25", "room": "Progress", "slug": "acud-2025-4480-fundamental-bottlenecks-for-ai-and-hpc", "url": "https://pretalx.surf.nl/acud-2025/talk/A8QYRM/", "title": "Fundamental bottlenecks for AI and HPC", "subtitle": "", "track": "Generative AI and Machine Learning", "type": "Short presentation with Q&A", "language": "en", "abstract": "Snellius and other HPC systems are not magic, even if it sometimes may feel so.\r\nEfficient usage of the available hardware is the difference between a model that may be just 'OK', or a model that is State-of-the-art (and I have examples in my pocket to prove it!).\r\nTrusting that whatever you throw at the system will be efficient 'automagically' is the quickest way to burn GPU hours without getting what you really want: breakthrough science!", "description": "Is your dataloader asleep at the wheel? Is over-eager logging killing your performance because it's forcing CPU<->GPU syncs? Does 100% GPU utilization actually mean that your GPU is being used effectively? (Hint: it's not!)  \r\nIn this talk we'll go over the fundamental bottlenecks of compute: those things in any HPC system that will cause your workflow to be slower than it needs to be, and what you can do to transform your workflow from 'it eventually works' to 'it works remarkably well'.", "recording_license": "", "do_not_record": false, "persons": [{"code": "TC7LJP", "name": "Robert-Jan Schlimbach", "avatar": "https://pretalx.surf.nl/media/avatars/TC7LJP_GTJLPCA.png", "biography": "I have been at SURF for 5 years as an AI+HPC advisor, helping AI researchers make GPUs go brrr on our National Supercomputer Snellius. Few parts of the intersection of AI+HPC remain a mystery to me, and as an aspiring wise old man I love to preach the gospel of efficiency to anyone that will listen.", "public_name": "Robert-Jan Schlimbach", "guid": "109a955a-c2a9-5ff7-b20e-ae7014308541", "url": "https://pretalx.surf.nl/acud-2025/speaker/TC7LJP/"}], "links": [], "feedback_url": "https://pretalx.surf.nl/acud-2025/talk/A8QYRM/feedback/", "origin_url": "https://pretalx.surf.nl/acud-2025/talk/A8QYRM/", "attachments": []}, {"guid": "8237d6e0-32ed-55fb-920a-555890d1326a", "code": "7YLTTZ", "id": 4406, "logo": null, "date": "2025-12-04T12:00:00+01:00", "start": "12:00", "duration": "00:25", "room": "Progress", "slug": "acud-2025-4406-no-gpu-required-training-and-using-scalable-llms-on-cpus", "url": "https://pretalx.surf.nl/acud-2025/talk/7YLTTZ/", "title": "No GPU required: Training and using scalable LLMs on CPUs", "subtitle": "", "track": "Generative AI and Machine Learning", "type": "Short presentation with Q&A", "language": "en", "abstract": "Transformer-based LLMs, at scale, are prohibitively expensive to train, requiring massive GPU capacity. Alternative technologies do exist, producing functionally equivalent LLMs at a fraction of the training costs, using high-memory CPU nodes. I will illustrate this with a memory-based LLM trained on Snellius' hi-mem nodes.", "description": "Memory-based language modeling, proposed by Van den Bosch (2005), is a machine learning approach to next-token prediction based on the k-nearest neighbor (k-NN) classifier (Aha, Kibler, and Albert, 1991; Daelemans and Van den Bosch, 2006a). This non-neural machine learning approach relies on storing all training data in memory, and generalizes from this training data when classifying unseen new data using similarity-based inference. Memory-based language modeling is functionally roughly equivalent to decoder Transformers (Vaswani et al., 2017), in the sense that both can run in autoregressive text generation mode and predict next tokens based on a certain amount of prior context.\r\n\r\nWhile training a memory-based language model is generally low-cost, as it involves a one-pass reading of training data and does not involve any convergence-based iterative training, a naive implementation would render it useless for inference. The upper-bound complexity of k-nearest neighbor classification is notoriously unfavorable, i.e. O(nd), where n is the number of examples in memory, and d is the number of features or dimensions (e.g. context size). However, improvements and fast approximations are available. Daelemans et al. (2010) offer a range of approximations offering fast classification and data compression using prefix tries. Another notable aspect of memory-based language modeling, as observed earlier by Van den Bosch (2006b), is that its next-word prediction performance increases log-linearly: with every 10-fold increase in the amount of training data, next-word prediction accuracy increases by a more or less constant amount (although there may be a plateau eventually which we never reached because of memory limitations).\r\n\r\nThe relatively costs in learning as well as inference make memory-based language modeling a potential eco-friendly alternative to the generally costly training of Transformer-based language models (Strubell, 2019). All experiments carried out so far with memory-based language models have been based on publicly available software, with TiMBL as the basic classification engine (https://github.com/LanguageMachines/timbl). All required scripts for training and inference are available on GitHub (https://github.com/antalvdb/memlm).\r\n\r\nReferences\r\n\r\nD. W. Aha, D. Kibler, and M. Albert. 1991. Instance-based learning algorithms. Machine Learning, 6:37\u2013\r\n66.\r\n\r\nW. Daelemans and A. Van den Bosch. 2005. Memory-based language processing. Cambridge University\r\nPress, Cambridge, UK.\r\n\r\nW. Daelemans, J. Zavrel, K. Van der Sloot, and A. Van den Bosch. 2010. TiMBL: Tilburg memory based\r\nlearner, version 6.3, reference guide. Technical Report ILK 10-01, ILK Research Group, Tilburg University.\r\n\r\nA. Van den Bosch. 2006a. Scalable classification-based word prediction and confusible correction. Traitement Automatique des Langues, 46(2):39\u201363.\r\n\r\nAntal van den Bosch. 2006b. All-word prediction as the ultimate confusible disambiguation. In Proceedings of the Workshop on Computationally Hard Problems and Joint Inference in Speech and Language Processing, pages 25\u201332, New York City, New York. Association for Computational Linguistics.\r\n\r\nAshish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, \u0141ukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. In Proceedings of the 31st International\r\nConference on Neural Information Processing Systems, NIPS\u201917, page 6000\u20136010, Red Hook, NY, USA. Curran Associates Inc.", "recording_license": "", "do_not_record": false, "persons": [{"code": "VLLNJF", "name": "Antal van den Bosch", "avatar": "https://pretalx.surf.nl/media/avatars/VLLNJF_5R3j4Jx.jpg", "biography": "In my research I develop machine learning and language technology. Most of my work involves the intersection of the two fields: computers that learn to understand and generate natural language, nowadays known as Generative AI and Large Language Models. The computational models that this work produces have all kinds of applications in other areas of scholarly research as well as in society and industry. They also link in interesting ways to theories and developments in linguistics, psycholinguistics, neurolinguistics, and sociolinguistics. I love multidisciplinary collaborations to make advances in all these areas.", "public_name": "Antal van den Bosch", "guid": "346f80e7-56d0-545d-9f19-0b162d584e15", "url": "https://pretalx.surf.nl/acud-2025/speaker/VLLNJF/"}], "links": [], "feedback_url": "https://pretalx.surf.nl/acud-2025/talk/7YLTTZ/feedback/", "origin_url": "https://pretalx.surf.nl/acud-2025/talk/7YLTTZ/", "attachments": []}, {"guid": "268a17c5-fdfd-5574-9419-d4056301f50c", "code": "WWKFUY", "id": 4443, "logo": null, "date": "2025-12-04T13:25:00+01:00", "start": "13:25", "duration": "00:10", "room": "Progress", "slug": "acud-2025-4443-energy-boost-mind-in-motion", "url": "https://pretalx.surf.nl/acud-2025/talk/WWKFUY/", "title": "Energy Boost: Mind in Motion", "subtitle": "", "track": "Plenary", "type": "Energizer", "language": "en", "abstract": "Right after lunch, Rob and Emiel invite you to engage your mind in an unexpected way.", "description": "Through a short, and interactive moment, they\u2019ll challenge how we perceive focus, logic, and awareness. Demonstrating that our brains might just be capable of more than we think.", "recording_license": "", "do_not_record": false, "persons": [{"code": "EGLXJZ", "name": "Rob en Emiel", "avatar": "https://pretalx.surf.nl/media/avatars/EGLXJZ_tDTD8ac.jpg", "biography": "Rob & Emiel are renowned for delivering high-impact performances at  corporate events, combining years of experience with an unmatched track record. As the most awarded magic duo in the Netherlands, they have won 14 national gold medals and uniquely claimed the prestigious Grand Prix three times. Internationally, they earned podium places at multiple World Championships and were crowned world\u2019s best mentalists in China. With performances in over 15 countries and appearances in more than 100 television episodes like Op1, HLF8, Barend & van Dorp, Jensen, Life & Cooking, De Wereld Draait Door en Pauw & Witteman. They bring professional excellence, technical perfection, and a proven wow-factor to every business stage.", "public_name": "Rob en Emiel", "guid": "91599dfd-a908-5c7c-bc1a-40afd72424fd", "url": "https://pretalx.surf.nl/acud-2025/speaker/EGLXJZ/"}], "links": [], "feedback_url": "https://pretalx.surf.nl/acud-2025/talk/WWKFUY/feedback/", "origin_url": "https://pretalx.surf.nl/acud-2025/talk/WWKFUY/", "attachments": []}, {"guid": "1ec1bf66-8d5b-5ba4-80a1-9e3a33b59d0e", "code": "MFYS89", "id": 4444, "logo": null, "date": "2025-12-04T13:35:00+01:00", "start": "13:35", "duration": "00:30", "room": "Progress", "slug": "acud-2025-4444-next-generation-applications-for-advancing-scientific-discovery", "url": "https://pretalx.surf.nl/acud-2025/talk/MFYS89/", "title": "Next-Generation Applications for Advancing\u00a0Scientific Discovery", "subtitle": "", "track": "Plenary", "type": "In Conversation", "language": "en", "abstract": "We are increasingly engaged in transdisciplinary research to address the complex challenges our world faces today, such as transitioning to renewable energy systems, advancing personalised medicine, leveraging digital twins, and accurately predicting climate change. Advanced research e-infrastructure has become essential for tackling these questions in an integrated manner. To achieve these ambitions, we are converging on using multiple technologies, methodologies, computing and data infrastructures, and software stacks to create sustainable, long-term value. In this respect, applications and workflows are crucial for addressing scientific challenges, achieving outcomes, and advancing the boundaries of research.", "description": "Engaging in discussions and debates about the future of workflows and applications is just as crucial for advancing research as conversations about infrastructure. It is essential to ensure this topic receives equal attention and support, especially when strategising on infrastructure planning and development, to provide a well-rounded approach that fosters innovation and collaboration.", "recording_license": "", "do_not_record": false, "persons": [{"code": "ZVFTVE", "name": "Sander Houweling", "avatar": "https://pretalx.surf.nl/media/avatars/ZVFTVE_CkuK5jz.jpeg", "biography": "Sander Houweling is Professor of Atmosphere, Greenhouse Gases, and Climate at the Department of Earth Sciences at Vrije Universiteit Amsterdam and a senior researcher at NWO-I SRON Space Research Organization Netherlands. His research focuses on long-lived greenhouse gases in the atmosphere and how these are influenced by human activities. His research group at VU Amsterdam develops numerical methods, implemented on high-performance computers, for monitoring greenhouse gas emissions using measurements from global and regional measurement networks and satellites. He is committed to the independent evaluation of national emission reports to the UNFCCC based on atmospheric data.", "public_name": "Sander Houweling", "guid": "26e10cb6-7932-53e3-bb9d-9834985b87f1", "url": "https://pretalx.surf.nl/acud-2025/speaker/ZVFTVE/"}, {"code": "ZAMUDV", "name": "Prof. Zeila Zanolli", "avatar": "https://pretalx.surf.nl/media/avatars/ZAMUDV_YFC5PWW.jpg", "biography": "Zeila Zanolli is leading the \u201cQuantum Materials by Design\u201d group at the Chemistry Department/Debye Institute for Nanomaterials Science, Utrecht University. Previously (2018 \u2013 2020) she was a Ramon y Cajal Fellow at ICN2, Barcelona (Spain), an excellence program of the Spanish Ministry for Economy, Industry and Competitiveness (MINECO). In 2016 \u2013 2018, she leaded the Nanospintronics Group at the Physics Dept of RWTH Aachen University, funded by the DFG. In 2015 \u2013 2012 she was Marie Curie Intra-European Fellow at Forschungszentrum J\u00fclich (Germany). \r\n\r\nHer research focus is on Quantum Materials, a class of materials in which quantum mechanical effects are visible at the macroscopic scale. They provide unprecedented opportunities to enable a new technology based on quantum effects, with impact on low-dissipation electronics, photovoltaics, quantum information and, in general, quantum engineering. Her major contribution are in developing and using first-principles theory and computational methods to investigate topological materials, superconductors, quantum transport, (magnetic) proximity interaction, and spectroscopy. Her group is core developer of the open source code SIESTA https://gitlab.com/siesta-project/ \r\n\r\n\r\nShe serves in the Psi-k working group \u201cQuantum materials driven by correlations, topology or spin\",  in the Steering Committee of the European Theoretical Spectroscopy Facility (ETSF), and in the board of the \u201cSemiconductor and Quantum Materials\u201d session of the European Physical Society. Since 2019 Dr. Zanolli serves in the Editorial College of SciPost Physics, a Diamond Open Access publication portal. In 2018-20, Dr. Zanolli served in the Executive Committee of the MaX (MAterials design at the eXascale) European Centre of Excellence which enables materials modelling, simulations, discovery and design at the frontiers of the current and future High Performance Computing (HPC), High Throughput Computing (HTC) and data analytics technologies.  In 2017 she has been elected Fellow of the Young Academy of Europe (YAE), a pan-European network of scientists active in science policy, where she served as a board member and treasurer in 2028-22.", "public_name": "Prof. Zeila Zanolli", "guid": "f878eea4-f21d-5a34-828b-436208e51a45", "url": "https://pretalx.surf.nl/acud-2025/speaker/ZAMUDV/"}, {"code": "B83H8P", "name": "Sagar Dolas", "avatar": "https://pretalx.surf.nl/media/avatars/B83H8P_UBiS8b0.jpg", "biography": "Sagar Dolas is Senior Advisor & Program Manager at SURF. He leads initiatives related to Advanced Computing and focuses on the future of applications and infrastructure for scientific research. He has a background in high-performance computing and applied mathematics.", "public_name": "Sagar Dolas", "guid": "5926f6d5-32e9-5686-8a2a-338250ac6360", "url": "https://pretalx.surf.nl/acud-2025/speaker/B83H8P/"}], "links": [], "feedback_url": "https://pretalx.surf.nl/acud-2025/talk/MFYS89/feedback/", "origin_url": "https://pretalx.surf.nl/acud-2025/talk/MFYS89/", "attachments": []}, {"guid": "aa54c0c7-dfbc-51c8-ab94-bddcb0eb8b68", "code": "MHUJHK", "id": 4420, "logo": null, "date": "2025-12-04T14:10:00+01:00", "start": "14:10", "duration": "00:25", "room": "Progress", "slug": "acud-2025-4420-tulip-a-prototype-for-open-locally-hosted-llm-infrastructure", "url": "https://pretalx.surf.nl/acud-2025/talk/MHUJHK/", "title": "TULIP: A Prototype for Open, Locally Hosted LLM Infrastructure", "subtitle": "", "track": "Generative AI and Machine Learning", "type": "Short presentation with Q&A", "language": "en", "abstract": "Large Language Models are becoming core research tools, yet dependence on commercial APIs raises issues of privacy, compliance, and long-term cost. At TU Delft, REIT and ICT are prototyping TULIP, a Kubernetes-based platform for locally hosted open LLMs. We\u2019ll share design choices that prioritize responsible innovation: containerized serving with an OpenAI-compatible API, cluster-native scaling, and transparent monitoring. \r\n\r\nWhile national initiatives like SURF\u2019s WiLLMa focus on shared capacity, TULIP explores the campus-level space: providing researchers with reproducible endpoints, model governance, and early feasibility metrics for institutional hosting. We will share early lessons, governance implications, and practical guidance for universities and labs aiming to offer sustainable, open alternatives to proprietary AI services.", "description": "TULIP is TU Delft\u2019s prototype for open, locally hosted LLM infrastructure. This session will highlight: - Why a local pilot like TULIP matters for researcher engagement - How it complements WiLLMa, SURF\u2019s AI hub initiative - Early lessons on balancing technical feasibility with governance and sustainability - Open discussion on how institutional platforms can provide sustainable, open alternatives to proprietary AI services The session is aimed at researchers, research engineers, and infrastructure managers curious about first steps in hosting open LLMs on institutional hardware", "recording_license": "", "do_not_record": false, "persons": [{"code": "YEFKXG", "name": "Azza Ahmed", "avatar": null, "biography": "", "public_name": "Azza Ahmed", "guid": "81cba1de-2731-5aa6-a898-aff9dbc4e4dd", "url": "https://pretalx.surf.nl/acud-2025/speaker/YEFKXG/"}], "links": [], "feedback_url": "https://pretalx.surf.nl/acud-2025/talk/MHUJHK/feedback/", "origin_url": "https://pretalx.surf.nl/acud-2025/talk/MHUJHK/", "attachments": []}, {"guid": "cd406a83-bed0-5c1c-b8ab-4831ab6ba44b", "code": "9LR7FS", "id": 4428, "logo": null, "date": "2025-12-04T15:25:00+01:00", "start": "15:25", "duration": "00:25", "room": "Progress", "slug": "acud-2025-4428-developing-robust-search-with-open-source-llms", "url": "https://pretalx.surf.nl/acud-2025/talk/9LR7FS/", "title": "Developing Robust Search with Open-Source LLMs", "subtitle": "", "track": "Generative AI and Machine Learning", "type": "Short presentation with Q&A", "language": "en", "abstract": "While open-source search models have greatly improved with transformer-based architectures, they face challenges outside their training domain, such as when applied to multi-modal or non-English text data. In this talk, we will describe some of our ongoing work developing new open-source models to address these challenges:\r\n\r\n- **Multilingual retrieval.** We train an effective multilingual sparse retrieval model achieving state-of-the-art performance on standard multilingual benchmarks while continuing to perform well in English. \r\n- **Multimodal retrieval.** We improve multimodal retrieval for the visual document retrieval task with an approach leveraging existing vision-language models. \r\n- **Complex retrieval.** We develop query expansion for complex information needs that cannot be handled well with standard methods. \r\n- **Synthetic data generation.** We explore synthetic data generation for enabling training and evaluation on broader scenarios like retrieval-augmented generation (RAG). \r\n- **Efficient retrieval models.** Given the increased computational costs of using LLMs for retrieval, we explore several strategies for improving their efficiency, including an effective pruning approach that results in smaller models with comparable performance and engineering work.", "description": "Our talk will describe our research on robust search with open source LLMs and briefly describe our engineering work developing a Triton kernel to speed up training and inference with learned sparse retrieval models, with both efforts leveraging the computational power of the LUMI supercomputer.", "recording_license": "", "do_not_record": false, "persons": [{"code": "KYAKRD", "name": "Dylan Ju", "avatar": null, "biography": "I am a PhD student at IRLab, Amsterdam. My research interests include representation learning and retrieval-augmented generation", "public_name": "Dylan Ju", "guid": "267e576c-e0dd-568c-a591-18c5759a118f", "url": "https://pretalx.surf.nl/acud-2025/speaker/KYAKRD/"}, {"code": "SQE9PT", "name": "Yibin Lei", "avatar": "https://pretalx.surf.nl/media/avatars/SQE9PT_yPyPqTd.jpg", "biography": "", "public_name": "Yibin Lei", "guid": "e5efe15c-26cb-5bc3-aa93-1ba869f17073", "url": "https://pretalx.surf.nl/acud-2025/speaker/SQE9PT/"}, {"code": "QGXNKE", "name": "Thong Nguyen", "avatar": null, "biography": "", "public_name": "Thong Nguyen", "guid": "1154621e-e4c6-536b-ac71-60e7791ed198", "url": "https://pretalx.surf.nl/acud-2025/speaker/QGXNKE/"}], "links": [], "feedback_url": "https://pretalx.surf.nl/acud-2025/talk/9LR7FS/feedback/", "origin_url": "https://pretalx.surf.nl/acud-2025/talk/9LR7FS/", "attachments": []}, {"guid": "de96facc-a1ac-56d7-b680-e0956f6f5e8c", "code": "VLWDSR", "id": 4445, "logo": null, "date": "2025-12-04T15:55:00+01:00", "start": "15:55", "duration": "00:20", "room": "Progress", "slug": "acud-2025-4445-technology-service-updates", "url": "https://pretalx.surf.nl/acud-2025/talk/VLWDSR/", "title": "Technology & Service Updates", "subtitle": "", "track": "Plenary", "type": "Technology & Service Updates", "language": "en", "abstract": "Get up to speed with the latest developments in advanced computing, services, and technology within SURF. This session offers a concise overview of what\u2019s new, what\u2019s changing, and how these innovations will support the community in the year ahead.", "description": "This session offers a concise overview of what\u2019s new, what\u2019s changing, and how these innovations will support the community in the year ahead.", "recording_license": "", "do_not_record": false, "persons": [{"code": "R9ANGE", "name": "Walter Lioen", "avatar": "https://pretalx.surf.nl/media/avatars/R9ANGE_TaBNr6I.jpg", "biography": "Walter Lioen is Domain Manager Research Services at SURF. He studied mathematics at the University of Amsterdam and began his career as a scientific programmer at CWI, where he used Dutch supercomputers to develop efficient numerical and computational algorithms. In 2001 he moved to Data Distilleries as a software engineer. Since 2007 he has worked at SURF, progressing from HPC consultant to team lead and department head. Walter has been closely involved in European supercomputing initiatives such as DEISA and PRACE, and he currently serves as vice-chair of EuroHPC\u2019s Infrastructure Advisory Group.", "public_name": "Walter Lioen", "guid": "d3fb72cf-8274-5471-b8a5-4183c1818724", "url": "https://pretalx.surf.nl/acud-2025/speaker/R9ANGE/"}], "links": [], "feedback_url": "https://pretalx.surf.nl/acud-2025/talk/VLWDSR/feedback/", "origin_url": "https://pretalx.surf.nl/acud-2025/talk/VLWDSR/", "attachments": []}, {"guid": "635dc303-b44f-5845-961b-729b128fae09", "code": "QN8AS7", "id": 4446, "logo": null, "date": "2025-12-04T16:15:00+01:00", "start": "16:15", "duration": "00:20", "room": "Progress", "slug": "acud-2025-4446-closing-experience", "url": "https://pretalx.surf.nl/acud-2025/talk/QN8AS7/", "title": "Closing Experience", "subtitle": "", "track": "Plenary", "type": "Closing Experience", "language": "en", "abstract": "This final moment isn\u2019t just a closing. It\u2019s a celebration, a lasting spark to carry with you beyond today. And when their act finishes, Valeriu will step back into the spotlight to guide us through the day\u2019s final reflections and officially bring the Advanced Computing User Day to a close.", "description": "This final moment isn\u2019t just a closing. It\u2019s a celebration, a lasting spark to carry with you beyond today.", "recording_license": "", "do_not_record": false, "persons": [{"code": "EGLXJZ", "name": "Rob en Emiel", "avatar": "https://pretalx.surf.nl/media/avatars/EGLXJZ_tDTD8ac.jpg", "biography": "Rob & Emiel are renowned for delivering high-impact performances at  corporate events, combining years of experience with an unmatched track record. As the most awarded magic duo in the Netherlands, they have won 14 national gold medals and uniquely claimed the prestigious Grand Prix three times. Internationally, they earned podium places at multiple World Championships and were crowned world\u2019s best mentalists in China. With performances in over 15 countries and appearances in more than 100 television episodes like Op1, HLF8, Barend & van Dorp, Jensen, Life & Cooking, De Wereld Draait Door en Pauw & Witteman. They bring professional excellence, technical perfection, and a proven wow-factor to every business stage.", "public_name": "Rob en Emiel", "guid": "91599dfd-a908-5c7c-bc1a-40afd72424fd", "url": "https://pretalx.surf.nl/acud-2025/speaker/EGLXJZ/"}, {"code": "WZQATP", "name": "Valeriu Codreanu", "avatar": "https://pretalx.surf.nl/media/avatars/WZQATP_0lulE3q.jpeg", "biography": "With more than 15 years of experience in high-performance computing, Valeriu Codreanu is a strategic leader known for combining vision with empathy and a strong commitment to advancing research infrastructure in the Netherlands and across Europe. As Head of High-Performance Computing & Visualization at SURF, he oversees the Dutch national supercomputer Snellius, manages a portfolio exceeding \u20ac20M annually, and leads a team of over 30 specialists driving innovation in advanced computing.\r\n\r\nHe plays a central role in shaping the next generation of national infrastructure, including the upcoming tender that will unify SURF\u2019s HPC, Grid, and Cloud services into a single, future-proof research platform. His influence extends across Europe through leadership positions in VSC Tier-1, LUMI, the Jules Verne exascale consortium, and the Dutch AI Factory.\r\n\r\nPassionate about people as much as technology, Valeriu Codreanu is dedicated to mentoring talent, empowering teams, and inspiring research communities to push boundaries and achieve lasting impact.", "public_name": "Valeriu Codreanu", "guid": "5522c8a3-4022-5559-a5cb-ceaee5a9594c", "url": "https://pretalx.surf.nl/acud-2025/speaker/WZQATP/"}], "links": [], "feedback_url": "https://pretalx.surf.nl/acud-2025/talk/QN8AS7/feedback/", "origin_url": "https://pretalx.surf.nl/acud-2025/talk/QN8AS7/", "attachments": []}], "Quest": [{"guid": "f0b08d31-04df-5112-901a-63e2aeda1573", "code": "NRV7JC", "id": 4461, "logo": null, "date": "2025-12-04T11:00:00+01:00", "start": "11:00", "duration": "00:25", "room": "Quest", "slug": "acud-2025-4461-accelerating-crispr-grna-efficiency-prediction-on-the-snellius-hpc-system", "url": "https://pretalx.surf.nl/acud-2025/talk/NRV7JC/", "title": "Accelerating CRISPR gRNA Efficiency Prediction on the Snellius HPC system", "subtitle": "", "track": "HPC for Societal and Industrial Impact", "type": "Short presentation with Q&A", "language": "en", "abstract": "CRISPR gene editing is transforming how we approach challenges in health, food, and sustainability,  but one question still slows everyone down: which guideRNA will actually work?", "description": "A guide RNA is the molecule that tells the CRISPR system where to cut or modify DNA. Predicting how well it performs is essential for everything from developing new therapies to improving crops or designing cleaner bioprocesses.\r\n\r\nFor my MSc project, I used the Snellius supercomputer at SURF, supported through the EuroCC Netherlands infrastructure, to test whether adding RNA structure information could make prediction models smarter. Scaling this workflow on HPC let me process tens of thousands of sequences, train deep-learning models efficiently, and keep every step reproducible.\r\n\r\nThe work shows how advanced computing can bridge scientific insight and industrial impact, illustrating how reproducible, large-scale AI workflows can drive innovation across sectors that depend on complex biological or experimental data.", "recording_license": "", "do_not_record": false, "persons": [{"code": "WZV3LQ", "name": "Sjoerd Kelder", "avatar": null, "biography": "Sjoerd Kelder is a data scientist specializing in scaling machine learning workflows on high-performance computing systems. For his MSc in Information Studies (UvA, 2025) he used SURF\u2019s Snellius HPC system to benchmark deep learning models with extended feature sets on large datasets. He now works with Fearless League on AI-powered lab tooling and reproducible ML infrastructure. His interests include workflow design, reproducibility practices, and efficient deployment of ML pipelines on large compute resources, applicable across sectors from science to industry. \r\n\r\nUniversity of Amsterdam (MSc Information Studies, 2025) / Fearless League (AI R&D)", "public_name": "Sjoerd Kelder", "guid": "f3c58ce8-c512-5dba-8329-9fd6449a1758", "url": "https://pretalx.surf.nl/acud-2025/speaker/WZV3LQ/"}], "links": [], "feedback_url": "https://pretalx.surf.nl/acud-2025/talk/NRV7JC/feedback/", "origin_url": "https://pretalx.surf.nl/acud-2025/talk/NRV7JC/", "attachments": []}, {"guid": "bc0a44ba-08b8-52d3-8eab-646b5c79a1a2", "code": "GF37TS", "id": 4450, "logo": null, "date": "2025-12-04T12:00:00+01:00", "start": "12:00", "duration": "00:25", "room": "Quest", "slug": "acud-2025-4450-benchmarking-delft3d-fm-on-hpc-systems-for-real-life-problems-in-surface-water", "url": "https://pretalx.surf.nl/acud-2025/talk/GF37TS/", "title": "Benchmarking Delft3D FM on HPC systems for real-life problems in surface water", "subtitle": "", "track": "HPC for Societal and Industrial Impact", "type": "Short presentation with Q&A", "language": "en", "abstract": "**Importance of Simulation of Surface Water Systems**\r\nForecasting of flooding, morphology and water quality in coastal and estuarine areas, rivers, and lakes is of great importance for society. To tackle this, the Delft3D Flexible Mesh Suite (Delft3D FM) has been developed by Deltares. Delft3D FM is used worldwide and consists of modules for modelling hydrodynamics, waves, morphology, water quality, and ecology.", "description": "**Need for HPC Optimization in Real-Life Applications**\r\nThere is urgency to make Delft3D FM more efficient and scalable for high performance computing for large scale models of real-life applications. The range of these applications is quite broad: from forecasting of flooding near the dikes to ecological impact assessments of wind parks and/or floating solar panels and from the design of harbours to large scale land reclamation projects. For that purpose, a small project focussed on new benchmarks to get an actual status of the parallel performance. These benchmarks of Delft3D FM were performed a.o. on Snellius from SURF for several typical real-life applications.\r\n\r\n**Use of Sixth-Generation Models and Snellius Benchmarks**\r\nSeveral selected cases are from the sixth-generation models for Rijkswaterstaat. These models are developed and under maintenance for a broad application range in the main Dutch waterbodies and used by other parties for applications also (requests via iplo.nl). On Snellius the Apptainer version of Delft3D FM was used for the benchmarks. Deltares offers maintenance and support for this Apptainer version, also in combination with the sixth-generation models. The Apptainer version of Delft3D FM is available also for other users of Snellius.", "recording_license": "", "do_not_record": false, "persons": [{"code": "FEENPV", "name": "Menno Genseberger", "avatar": "https://pretalx.surf.nl/media/avatars/FEENPV_GOxsJ77.jpg", "biography": "Menno Genseberger studied mathematics and physics at the University of Amsterdam. PhD research at Utrecht University and CWI was on domain decomposition to enable HPC for large scale eigenvalue problems from plasma physics and oceanography.\r\n\r\nHe joined Deltares in 2002. First by developing simulation software for surface water. He gave also lead to a discipline numerical methods. Later focus shifted to coupled hydrodynamical and transport modelling for lakes. In 2010 he initiated a pilot on HPC for Deltares at SURF. The years that followed this resulted in several European projects in which Deltares and SURF collaborated on HPC for simulation software of surface water.", "public_name": "Menno Genseberger", "guid": "1517ce3b-9891-5e47-bfbb-eea92e5aa28b", "url": "https://pretalx.surf.nl/acud-2025/speaker/FEENPV/"}], "links": [], "feedback_url": "https://pretalx.surf.nl/acud-2025/talk/GF37TS/feedback/", "origin_url": "https://pretalx.surf.nl/acud-2025/talk/GF37TS/", "attachments": []}, {"guid": "4e8b5226-9579-54f7-bb6d-9d93dbf1fb3c", "code": "RJ8H93", "id": 4447, "logo": null, "date": "2025-12-04T14:10:00+01:00", "start": "14:10", "duration": "00:50", "room": "Quest", "slug": "acud-2025-4447-romeo-hpc-center-missions-and-projects", "url": "https://pretalx.surf.nl/acud-2025/talk/RJ8H93/", "title": "ROMEO HPC center: missions and projects", "subtitle": "", "track": "HPC for Societal and Industrial Impact", "type": "Interactive Presentation with Conversation & Input", "language": "en", "abstract": "ROMEO HPC Center of University of Reims, under the lead of Teratec, is partner of the French National Competence Center.", "description": "ROMEO HPC Center hosts one of the most powerful academic supercomputer in France. We will present the ecosystem of the HPC center, the supercomputer itself and the other infrastructures as well as our participation in national and European projects.", "recording_license": "", "do_not_record": false, "persons": [{"code": "3B798K", "name": "Florence Draux", "avatar": "https://pretalx.surf.nl/media/avatars/3B798K_cnB73dF.jpg", "biography": "Florence Draux obtained a PhD in molecular biophysics from University of Reims (France). Then she held research engineer position at University of Reims for 3 years. She then started a career in high school education for 12 years. In 2023, she joined University of Reims ROMEO Computer Center as a research engineer and she is responsible for industrial partnerships.", "public_name": "Florence Draux", "guid": "9b2b022a-c050-58ac-b8cc-edd767a8357e", "url": "https://pretalx.surf.nl/acud-2025/speaker/3B798K/"}, {"code": "R7TRE9", "name": "Fr\u00e9d\u00e9ric Maugui\u00e8re", "avatar": "https://pretalx.surf.nl/media/avatars/R7TRE9_UdgBoEx.jpg", "biography": "Fr\u00e9d\u00e9ric Maugui\u00e8re obtained a PhD in mathematical physics from University of Reims (France) in the field of molecular physics and dynamical systems. Then he held postdoctoral positions at University of Crete (Greece) and University of Bristol (UK) working on several aspects of transition state theory. After working for several companies in the private sector for a few years, he joined University of Reims ROMEO Computer Center in 2018 as a research engineer.", "public_name": "Fr\u00e9d\u00e9ric Maugui\u00e8re", "guid": "9a557b34-b98f-5b1e-802c-f0320ade07e7", "url": "https://pretalx.surf.nl/acud-2025/speaker/R7TRE9/"}], "links": [], "feedback_url": "https://pretalx.surf.nl/acud-2025/talk/RJ8H93/feedback/", "origin_url": "https://pretalx.surf.nl/acud-2025/talk/RJ8H93/", "attachments": []}], "Expedition": [{"guid": "04edd1d2-90cf-5b29-b8b1-40d4cd240cd4", "code": "7FHCNZ", "id": 4432, "logo": null, "date": "2025-12-04T11:00:00+01:00", "start": "11:00", "duration": "00:25", "room": "Expedition", "slug": "acud-2025-4432-unveiling-the-radio-sky-high-resolution-lofar-imaging-with-advanced-computing", "url": "https://pretalx.surf.nl/acud-2025/talk/7FHCNZ/", "title": "Unveiling the Radio Sky: High-Resolution LOFAR Imaging with Advanced Computing", "subtitle": "", "track": "Data Processing & Cloud Solutions", "type": "Short presentation with Q&A", "language": "en", "abstract": "LOFAR, Europe\u2019s powerful low-frequency radio telescope, produces vast amounts of data, making high-resolution imaging a major challenge. Thanks to new algorithms, SURF\u2019s Spider platform, and AI expertise, researchers now achieve unprecedented detail, delivering the sharpest LOFAR images of the Universe so far.", "description": "LOFAR is a low-frequency radio telescope composed of thousands of simple antennas distributed across Europe, with most located in the north of the Netherlands. By combining signals from these stations, LOFAR can in principle deliver extremely high-resolution images over large regions of the sky. Achieving this, however, is highly challenging: the telescope generates massive data volumes that require complex calibration and imaging algorithms. Without careful calibration, the resulting images remain severely blurred.\r\n\r\nAnother hurdle is the computational expense, as single observations can produce images exceeding 10 gigapixels. These challenges long prevented imaging at LOFAR\u2019s full theoretical resolution. Recently, by developing new algorithms and exploiting SURF\u2019s high-throughput processing platform Spider, operated by the Distributed Data Processing team, together with SURF\u2019s AI expertise from the High-Performance Machine Learning team, we have overcome these barriers\u2014producing the deepest, highest-resolution LOFAR images of the Universe to date.", "recording_license": "", "do_not_record": false, "persons": [{"code": "HKRBSM", "name": "Reinout van Weeren", "avatar": null, "biography": "", "public_name": "Reinout van Weeren", "guid": "a6e3bb00-78e8-5148-940a-edf9adea91ca", "url": "https://pretalx.surf.nl/acud-2025/speaker/HKRBSM/"}], "links": [], "feedback_url": "https://pretalx.surf.nl/acud-2025/talk/7FHCNZ/feedback/", "origin_url": "https://pretalx.surf.nl/acud-2025/talk/7FHCNZ/", "attachments": []}, {"guid": "034cd7f6-26d2-534b-912e-2619de6442f6", "code": "XTPDP7", "id": 4430, "logo": null, "date": "2025-12-04T11:30:00+01:00", "start": "11:30", "duration": "00:25", "room": "Expedition", "slug": "acud-2025-4430-spaceborne-air-sea-heat-flux-enabled-with-spider", "url": "https://pretalx.surf.nl/acud-2025/talk/XTPDP7/", "title": "Spaceborne air-sea heat flux enabled with Spider", "subtitle": "", "track": "Data Processing & Cloud Solutions", "type": "Short presentation with Q&A", "language": "en", "abstract": "We live in a golden age of satellite remote sensing. The European Space Agency's Sentinel program in particular, which focuses on spaceborne Earth observation (EO), has set the standard for continuous, free and readily available satellite observations and products. The archive of EO data is vast, and continues to grow by many petabytes a year. From a scientific perspective, these vast quantities enable ever more research to be conducted, especially in the age of data-hungry artifical intelligence. Yet, without special infrastructure, the sheer magnitude of satellite data causes it to become unwieldly. Cloud-hosted services tailored to satellite data exist (noteably Google Earth Engine), but these tend to have their own shortcomings, such as limited availability of low-level (raw) satellite observations. \r\n\r\nIn our research group we study the ocean surface with spaceborne radars. Radars are uniquely capable for ocean monitoring: when mounted on a satellite they provide large coverage while being mostely unaffected by atmospheric interference (e.g. they can look through clouds), and the signals reflecting from the ocean surface provide all sorts of geophysical insights that are used in meteorology, storm tracking, swell predictions, and much more. But when looking at high resolution radar imagery of the ocean, one can identify a wealth of atmospheric information that is commonly ignored. Thus, we set about developing a methodology for extracting this information, focusing on the heat-flux exchange between the ocean and atmosphere---a critical climate variable for which no satellite products are available---from Sentinel-1's entire 10+ year data catalogue. \r\n\r\nIn this presentation we will outline the development of our methodology, which we call FluxSAR, and share preliminary scientific results. The presentation focuses on the challenges involved in working with the petabytes of high-resolution radar data, and how SURF's Spider HPC has enabled us to tackle these challenges head on.", "description": "1. Need for air-sea flux information\r\n2. Utilizing existing remote sensing data\r\n3. Too much data, HPC needed\r\n4. Spider to the rescue", "recording_license": "", "do_not_record": false, "persons": [{"code": "NJ3NDV", "name": "Owen O'Driscoll", "avatar": "https://pretalx.surf.nl/media/avatars/NJ3NDV_kcb982U.jpeg", "biography": "Owen received the master\u2019s degree in 2021 from the Civil Engineering Faculty, Delft University of Technology, where he is currently pursuing the Ph.D. degree in radar oceanography as part of the Geoscience and Remote Sensing department. From 2022 to 2023, he was with the Oceanography from Space Laboratory at Ifremer, Plouzan\u00e9 (France), to study air-sea interactions with spaceborne radars.", "public_name": "Owen O'Driscoll", "guid": "bc35688c-8854-51d9-ad80-a4793307c87a", "url": "https://pretalx.surf.nl/acud-2025/speaker/NJ3NDV/"}], "links": [], "feedback_url": "https://pretalx.surf.nl/acud-2025/talk/XTPDP7/feedback/", "origin_url": "https://pretalx.surf.nl/acud-2025/talk/XTPDP7/", "attachments": []}, {"guid": "223b0b1b-e0b7-5353-9f4e-c30b8a79557a", "code": "XBGRDU", "id": 4481, "logo": null, "date": "2025-12-04T14:10:00+01:00", "start": "14:10", "duration": "00:25", "room": "Expedition", "slug": "acud-2025-4481-modern-data-lakehouse-for-research", "url": "https://pretalx.surf.nl/acud-2025/talk/XBGRDU/", "title": "Modern Data Lakehouse for Research", "subtitle": "", "track": "Data Processing & Cloud Solutions", "type": "Short presentation with Q&A", "language": "en", "abstract": "SURF will start next year to investigate a Data Lakehouse, among others to explore its application in scientific workflows.", "description": "I will briefly discuss the concept of Data Lakehouse, its architecture and components. One of their characteristics is that they have some functionality like consistency similar to a Data warehouse, but they can process unstructured and semi-structured data. We did already some investigations in a number of projects encompassing scientific fields such as earth observation, sentiment analysis, and bio-imaging. I will share some preliminary insights to what kind of scientific use workflows it can be applied. And will show how we can use the various Data Lakehouse components in the workflow. The talk will also touch upon commercial solutions like Data Bricks that have full stack, including an ML-ops component, and open source solutions.      \r\n\r\nI will share some preliminary insights to what kind of scientific use workflows it can be applied. And will show how we can use the various Data Lakehouse components in the workflow. The talk will also touch upon commercial solutions like Data Bricks that have full stack, including an ML-ops component, and open source solutions.", "recording_license": "", "do_not_record": false, "persons": [{"code": "KKHKZL", "name": "Robert Griffioen", "avatar": null, "biography": "Robert Griffioen has a background in Artificial Intelligence. He did a Ph.D. about brain modelling with neural networks and a postdoc about large scale agent based simulations in an European project. After that he worked as a Business Intelligent consultant for a few years. Then he worked at Statistic Netherlands (Centraal Bureau for the Statistiek) in IT and Research for almost 10 years. Finally, he landed at SURF as among others a project manager, product manager and cloud solution architect for scientific projects.", "public_name": "Robert Griffioen", "guid": "50521cdf-010b-5b05-bf2b-b40374f34e91", "url": "https://pretalx.surf.nl/acud-2025/speaker/KKHKZL/"}], "links": [], "feedback_url": "https://pretalx.surf.nl/acud-2025/talk/XBGRDU/feedback/", "origin_url": "https://pretalx.surf.nl/acud-2025/talk/XBGRDU/", "attachments": []}, {"guid": "dd92f4c3-a283-5c69-87dd-e9e3504824e1", "code": "QKLGP7", "id": 4427, "logo": null, "date": "2025-12-04T15:25:00+01:00", "start": "15:25", "duration": "00:25", "room": "Expedition", "slug": "acud-2025-4427-spectrum-technical-blueprint-and-strategic-agenda-delivering-europe-s-roadmap-for-exabyte-scale-scientific-infrastructure", "url": "https://pretalx.surf.nl/acud-2025/talk/QKLGP7/", "title": "SPECTRUM Technical Blueprint and Strategic Agenda: Delivering Europe's Roadmap for Exabyte-Scale Scientific Infrastructure", "subtitle": "", "track": "Data Processing & Cloud Solutions", "type": "Short presentation with Q&A", "language": "en", "abstract": "This presentation introduces the public draft of SPECTRUM's Technical Blueprint and Strategic Research, Innovation and Deployment Agenda (SRIDA) for European data-intensive science infrastructure. The Technical Blueprint addresses the technical aspects whilst the SRIDA defines the strategic and policy dimensions of a unified European compute and data continuum. Both are based on comprehensive requirements analysis from High-Energy Physics and Radio Astronomy communities, including HL-LHC's exabyte-scale data processing, SKA's unprecedented computational demands, and LOFAR's distributed data processing challenges. We invite the advanced computing community to provide feedback during the open consultation phase to ensure the final documents address the research infrastructure needs.", "description": "The SPECTRUM project has developed a comprehensive framework for Europe's next-generation research infrastructure to support exabyte-scale scientific computing. \r\n\r\nThe Technical Blueprint addresses the fragmentation of current European computing resources by proposing an integrated technical architecture spanning. The SRIDA provides actionable priorities, implementation roadmaps, and policy recommendations for policymakers, infrastructure providers, and research communities. Together, they define both the technical capabilities and strategic governance needed for seamless workload migration across heterogeneous infrastructure whilst maintaining sovereignty and reducing environmental impact.\r\n\r\nThis presentation will outline the key architectural components, strategic priorities, and implementation pathways emerging from our community-driven analysis. We are currently in the open consultation phase and actively solicit feedback from the advanced computing community to ensure the final blueprint and agenda address the research community needs, helping shape Europe's strategic approach to exascale scientific infrastructure.\r\n\r\nFor more information: www.spectrumproject.eu", "recording_license": "", "do_not_record": false, "persons": [{"code": "CMFJVW", "name": "Sergio Andreozzi", "avatar": "https://pretalx.surf.nl/media/avatars/CMFJVW_plcNmii.jpg", "biography": "Sergio Andreozzi is the Head of Strategy, Innovation, and Communications at the EGI Foundation, which coordinates the EGI Federation to deliver advanced computing services to global research communities. In this role, Sergio leads EGI\u2019s strategy development, innovation management, and governance initiatives. He also serves as Project Director of the EC-funded SPECTRUM project. Sergio holds an Executive Master in Research Infrastructure Management from the University of Milano-Bicocca, a PhD in Computer Science from the University of Bologna, and an MSc in Computer Science Engineering from the University of Pisa.", "public_name": "Sergio Andreozzi", "guid": "b7169c10-c2c4-5bd1-9a3d-c3be5fb7f4a7", "url": "https://pretalx.surf.nl/acud-2025/speaker/CMFJVW/"}], "links": [], "feedback_url": "https://pretalx.surf.nl/acud-2025/talk/QKLGP7/feedback/", "origin_url": "https://pretalx.surf.nl/acud-2025/talk/QKLGP7/", "attachments": []}], "Mission 1": [{"guid": "e6f9fbc2-e702-5722-bb6a-3341e4da341a", "code": "3JX3NH", "id": 4431, "logo": null, "date": "2025-12-04T11:00:00+01:00", "start": "11:00", "duration": "00:25", "room": "Mission 1", "slug": "acud-2025-4431-intertwin-advancing-scientific-digital-twins-through-ai-federated-computing-and-data", "url": "https://pretalx.surf.nl/acud-2025/talk/3JX3NH/", "title": "interTwin: Advancing Scientific Digital Twins through AI, Federated Computing and Data", "subtitle": "", "track": "Innovative Technologies & Services", "type": "Short presentation with Q&A", "language": "en", "abstract": "Digital Twins (DT), highly accurate virtual representations of physical entities, have revolutionized industries by integrating numerical simulations and observational data to create realistic, dynamic models. Initially developed for industrial applications, digital twins have expanded into diverse domains. They enable accurate predictions by simulating real-world performance, identifying potential issues, and iterating feedback loops for optimized decision-making. This paradigm leverages advanced computational techniques to enhance our understanding and management of complex systems. The Horizon Europe  interTwin project has  developed a highly generic Digital Twin Engine (DTE) to support interdisciplinary Digital Twins(DT). The project brought together infrastructure providers, technology providers and DT use cases from different domains. This group of experts enables the co-design of both the DTE Blueprint Architecture and the prototype platform; not only benefiting end users like scientists and policymakers but also DT developers. The main contributions of the DTE are: (1) a federated architecture that allows seamless integration of distributed computing and storage resources across various institutions, (2) standardized interfaces and protocols that support interoperability among different scientific fields, (3) a co-design approach that includes requirements from high-energy physics, radio astronomy, gravitational-wave astrophysics, climate research, and environmental monitoring, and (4) strong methods for assessing AI model quality, provenance, and uncertainty measurement in federated settings. \r\nThe talk will focus on the DTE software components developed and integrated, detailing some of the pilot use cases that have successfully driven the DTE implementation.", "description": "Digital Twins (DT), highly accurate virtual representations of physical entities, have revolutionized industries by integrating numerical simulations and observational data to create realistic, dynamic models. Initially developed for industrial applications, digital twins have expanded into diverse domains. They enable accurate predictions by simulating real-world performance, identifying potential issues, and iterating feedback loops for optimized decision-making. This paradigm leverages advanced computational techniques to enhance our understanding and management of complex systems. The Horizon Europe  interTwin project has  developed a highly generic Digital Twin Engine (DTE) to support interdisciplinary Digital Twins(DT). The project brought together infrastructure providers, technology providers and DT use cases from different domains. This group of experts enables the co-design of both the DTE Blueprint Architecture and the prototype platform; not only benefiting end users like scientists and policymakers but also DT developers. The main contributions of the DTE are: (1) a federated architecture that allows seamless integration of distributed computing and storage resources across various institutions, (2) standardized interfaces and protocols that support interoperability among different scientific fields, (3) a co-design approach that includes requirements from high-energy physics, radio astronomy, gravitational-wave astrophysics, climate research, and environmental monitoring, and (4) strong methods for assessing AI model quality, provenance, and uncertainty measurement in federated settings. \r\nThe talk will focus on the DTE software components developed and integrated, detailing some of the pilot use cases that have successfully driven the DTE implementation.", "recording_license": "", "do_not_record": false, "persons": [{"code": "DLAAST", "name": "Andrea Manzi", "avatar": null, "biography": "", "public_name": "Andrea Manzi", "guid": "620c0ef0-89ab-525c-b973-6ef186d316cb", "url": "https://pretalx.surf.nl/acud-2025/speaker/DLAAST/"}], "links": [], "feedback_url": "https://pretalx.surf.nl/acud-2025/talk/3JX3NH/feedback/", "origin_url": "https://pretalx.surf.nl/acud-2025/talk/3JX3NH/", "attachments": []}, {"guid": "ed7e40bb-2ec9-54c2-ace6-d901f3a450df", "code": "Y8REXW", "id": 4425, "logo": null, "date": "2025-12-04T11:30:00+01:00", "start": "11:30", "duration": "00:50", "room": "Mission 1", "slug": "acud-2025-4425-ear-energy-aware-runtime-dashboard-workshop", "url": "https://pretalx.surf.nl/acud-2025/talk/Y8REXW/", "title": "EAR (Energy Aware Runtime) dashboard workshop", "subtitle": "", "track": "Innovative Technologies & Services", "type": "Workshop", "language": "en", "abstract": "Have you ever wondered how much energy your research on Snellius uses? Or maybe how performant or efficient your application is on Snellius? We at SURF did as well. This is why we have developed an end-user friendly, interactive, dashboard that allows you to display the energy usage of your jobs on Snellius and gives you insight into how well your application is using Snellius. This dashboard gives researchers the tools and visualizations for energy aware computing.", "description": "We at the HPCV-team at SURF have developed an end-user (researcher) focused energy dashboard that displays an overview of the energy statistics and efficiency metrics of jobs that are submitted to the supercomputer. This dashboard is built to display metrics that are collected from the EAR (Energy Aware Runtime) software which provides energy management, accounting and optimization for supercomputers. With the interactive figures that are displayed, end users should be able to gain insight into their energy footprint of their research, and what they can do about it to reduce or optimize their energy usage. In this workshop we want to give an introduction into the usage of EAR and the EAR dashboard. To get the full potential out of this workshop we recommend the attendees to run their own jobs and analyze their energy usage. This workshop is geared to every expertise level.", "recording_license": "", "do_not_record": false, "persons": [{"code": "YAMLD3", "name": "Casper van Leeuwen", "avatar": "https://pretalx.surf.nl/media/avatars/VD_201904170256_scaled_jpaYQfZ.jpg", "biography": "For the past 10 years I have been a visualization advisor at SURF. During my time at SURF, I came in touch with the many categories of visualization, through many educational and research fields. The one thing that stuck out to me the most and proved to be the most useful, was creating web-based 3D visualizations. Naturally, due to curiosity, interest from our members and my affinity to 3D content, XR grew to be a part of the work I do at SURF.", "public_name": "Casper van Leeuwen", "guid": "2b73f267-7a2c-56f0-becc-b9d9088619fe", "url": "https://pretalx.surf.nl/acud-2025/speaker/YAMLD3/"}], "links": [], "feedback_url": "https://pretalx.surf.nl/acud-2025/talk/Y8REXW/feedback/", "origin_url": "https://pretalx.surf.nl/acud-2025/talk/Y8REXW/", "attachments": []}, {"guid": "3a1e4d0a-38e1-531e-a2c5-f1e20ad69de4", "code": "Q8H8RN", "id": 4411, "logo": null, "date": "2025-12-04T14:10:00+01:00", "start": "14:10", "duration": "00:50", "room": "Mission 1", "slug": "acud-2025-4411-how-can-a-community-driven-approach-improve-competences-in-energy-efficient-scientific-computing-in-the-netherlands", "url": "https://pretalx.surf.nl/acud-2025/talk/Q8H8RN/", "title": "How can a community-driven approach improve competences in energy-efficient scientific computing in the Netherlands?", "subtitle": "", "track": "Innovative Technologies & Services", "type": "Interactive Presentation with Conversation & Input", "language": "en", "abstract": "This session aims to explore the feasibility of a community-driven approach to foster energy-efficient scientific computing in the Netherlands. By engaging researchers, support staff, and infrastructure providers, such an initiative can establish a self-sustaining Community of Practice, create an open knowledge base with practical training on energy monitoring and reduction in scientific computing, and organize nationwide training sessions to build foundational expertise. Together, these actions can complement infrastructure-level efficiency improvements with user-level practices, advancing sustainable and environmentally responsible research. A soon-to-be-launched initiative supported by TDCC-NES seeks to do this in the Natural and Engineering Sciences (NES) domain. During the session, participants will have the opportunity to learn more about the initiative, share feedback, and discuss ways to expand its impact to other scientific domains in the Netherlands.", "description": "The growing energy demands of scientific computing present significant challenges for environmental sustainability, particularly in disciplines that rely on large-scale, compute-intensive methods. Although advances in energy-efficient hardware and infrastructure have been made, researchers often remain unaware of the energy consumption and environmental impact of their computational tasks. This lack of awareness is largely due to the absence of systematic energy reporting from infrastructure providers and the limited availability of monitoring tools that allow task-level assessment. Additionally, current scientific computing frameworks typically do not offer pre-execution energy estimates, limiting researchers\u2019 ability to make informed trade-offs between performance and energy efficiency. As a result, without appropriate tools and expertise to measure and interpret energy use, researchers cannot fully evaluate the environmental footprint of their work or implement practices that support sustainable computing.\r\n\r\nIn this session, we aim to explore the potential of a community-driven approach to raise awareness and encourage the adoption of energy-efficient practices in the Netherlands. By engaging research organizations, support institutions, and infrastructure providers, such a collaborative effort can pursue three interconnected objectives to foster a culture of energy-conscious computing: (1) establish a self-sustaining Community of Practice, where researchers, support staff, and infrastructure providers collaboratively share and advance best practices for energy-efficient computing; (2) develop an open knowledge base offering training on practical tools and methods for monitoring and reducing energy consumption; and (3) organize a nationwide series of training sessions to build foundational expertise in energy-efficient computing among researchers and support staff. Together, these initiatives can complement ongoing infrastructure-level efficiency improvements with user-level practices, advancing the broader goal of sustainable and environmentally responsible research. During the session, we will present a soon-to-be-launched initiative supported by the TDCC-NES, designed to improve competences in energy-efficient scientific computing within the Natural and Engineering Sciences (NES) domain, and gather ideas and feedback from participants for expanding its impact to other domains across the Netherlands.", "recording_license": "", "do_not_record": false, "persons": [{"code": "PTQXDE", "name": "Dr. Serkan Girgin", "avatar": "https://pretalx.surf.nl/media/avatars/Girgin-Passport-Photo_CYCjrxI.jpg", "biography": "Dr. Serkan Girgin is an Associate Professor in the Geo-information Processing Department at the Faculty of Geo-information Science and Earth Observation (ITC), University of Twente. He has established and is currently leading ITC's Center of Expertise in Big Geodata Science (CRIB), a facility dedicated to advancing geospatial big data and cloud computing technologies by developing, collecting, and sharing operational expertise.  \r\n\r\nDr. Girgin's current research focuses on big data and cloud computing tools and infrastructures, with a particular emphasis on optimizing the performance and energy efficiency of geocomputing workflows. He provides strategic advice and consultancy on adopting these technologies for education, research, and capacity-building initiatives. He is also an expert in industrial risk assessment, more specificially technological accidents triggered by natural disasters. Besides developing methodologies, he also designed and developed the European Commission\u2019s Natech Database (eNatech), and the Rapid Natech Risk Assessment and Mapping System (RAPID-N).\r\n\r\nIn addition to his research, Dr. Girgin designs and develops tools and platforms that promote best practices in research software development and research data management, including fairly toolset, Open Data Explorer, and OpenSTAC. With over 30 years of experience in software development, his expertise spans geocomputing platforms, GIS and remote sensing applications, environmental information systems, and large-scale web applications.  \r\n\r\nDr. Girgin is a member of the ESA DestinE Sounding Board in the Netherlands, an eScience Center Fellow, and was named the SURF Research Support Champion in the Netherlands.\r\n\r\nhttps://linkedin.com/in/serkan-girgin", "public_name": "Dr. Serkan Girgin", "guid": "a1074ad7-7e73-54ea-aa31-14fa31c52278", "url": "https://pretalx.surf.nl/acud-2025/speaker/PTQXDE/"}, {"code": "TBWC8J", "name": "Bhawiyuga, Adhitya (UT-ITC)", "avatar": "https://pretalx.surf.nl/media/avatars/TBWC8J_B97XpCc.jpg", "biography": "Adhitya is a PhD candidate at the Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, specializing in Geo-information Processing. His research, in collaboration with The Center of Expertise in Big Geodata Science (CRIB), focuses on energy-e\ufb03ciency on earth observation big data processing within cloud computing environmet. He holds an M.Sc. in Logistics Information Technology from Pusan National University, Korea (2013) with the focus on vehicle-to-vehicle wireless communication. For the past 10 years, Adhitya has worked as a lecturer and researcher at the Faculty of Computer Science, Universitas Brawijaya, Indonesia. His experience includes collaborating on national and international projects such as the Indonesia Matching Fund Project, Erasmus+ Micro-Credential, and NICT ASEAN IVO Project. Beyond his primary research, Adhitya has developed a keen interest in the intersection of cloud computing service orchestration and scientific big data processing, particularly in the geospatial domain.", "public_name": "Bhawiyuga, Adhitya (UT-ITC)", "guid": "1c643183-044c-5d46-9d27-8a4f416ba35b", "url": "https://pretalx.surf.nl/acud-2025/speaker/TBWC8J/"}], "links": [], "feedback_url": "https://pretalx.surf.nl/acud-2025/talk/Q8H8RN/feedback/", "origin_url": "https://pretalx.surf.nl/acud-2025/talk/Q8H8RN/", "attachments": []}, {"guid": "d6f606e9-b430-5d29-98e5-9ed0f8a7e434", "code": "D7WK9G", "id": 4423, "logo": null, "date": "2025-12-04T15:25:00+01:00", "start": "15:25", "duration": "00:25", "room": "Mission 1", "slug": "acud-2025-4423-visualization-support-from-surf-on-snellius-and-beyond", "url": "https://pretalx.surf.nl/acud-2025/talk/D7WK9G/", "title": "Visualization support from SURF on Snellius (and beyond)", "subtitle": "", "track": "Innovative Technologies & Services", "type": "Short presentation with Q&A", "language": "en", "abstract": "An overview of the data visualization options that are available from SURF, including usage of Snellius and other infrastructure, plus available support from SURF for visualization projects.", "description": "This presentation will touch upon a few technical topics such as remote visualization, OpenOnDemand and GPU usage. We will also talk about a few non-technical things such as high-level workflows, support and courses. Finally, we show some visualization examples.", "recording_license": "", "do_not_record": false, "persons": [{"code": "GVK9X8", "name": "Paul Melis", "avatar": "https://pretalx.surf.nl/media/avatars/me-xr3_xyXwzwU.jpg", "biography": "Paul Melis is senior visualization advisor in the High-Performance Computing & Visualization group at SURF, having worked at SURFsara and SARA since 2009. He supports HPC users with (data) visualization, providing software & documentation, courses and working on visualization projects.\r\n\r\nApart from an HPC focus he spends part of his time on XR innovation within SURF. His XR activities include keeping tracking of hardware, software and market developments, trend watching, coordinating the [SURF XR Developer Network](https://www.surf.nl/en/xr-developer-network), providing technical input and giving XR demonstrations.", "public_name": "Paul Melis", "guid": "15eaa538-98c3-5e70-852e-8d51fc4bc6da", "url": "https://pretalx.surf.nl/acud-2025/speaker/GVK9X8/"}], "links": [], "feedback_url": "https://pretalx.surf.nl/acud-2025/talk/D7WK9G/feedback/", "origin_url": "https://pretalx.surf.nl/acud-2025/talk/D7WK9G/", "attachments": []}], "Mission 2": [{"guid": "3513dc8e-5f18-5e77-82e6-c564cdee2d95", "code": "Z7DXLP", "id": 4416, "logo": null, "date": "2025-12-04T11:00:00+01:00", "start": "11:00", "duration": "00:25", "room": "Mission 2", "slug": "acud-2025-4416-accelerating-mpi-amrvac-on-snellius-and-lumi", "url": "https://pretalx.surf.nl/acud-2025/talk/Z7DXLP/", "title": "Accelerating MPI-AMRVAC on Snellius and LUMI", "subtitle": "", "track": "High Performance Computing", "type": "Short presentation with Q&A", "language": "en", "abstract": "[MPI-AMRVAC](https://amrvac.org) is a parallel adaptive mesh refinement framework aimed at solving partial differential equations by a number of different numerical schemes. It is written in Fortran 90 and uses MPI for parallelisation across many CPUs.\r\n\r\nIn modern HPC infrastructure, most compute power is however not in the CPUs but in accelerators such as GPUs. In order to make use of this compute power, we have enabled MPI-AMRVAC to run on GPUs using OpenACC, enabling larger-scale simulations than ever before.\r\n\r\nI will discuss the advantages and challenges of OpenACC in our experience, and highlight the achieved performance improvement in MPI-AMRVAC on both Snellius and LUMI.", "description": "[MPI-AMRVAC](https://amrvac.org) is a parallel adaptive mesh refinement framework aimed at solving partial differential equations by a number of different numerical schemes. It is written in Fortran 90 and uses MPI for parallelisation across many CPUs.\r\n\r\nIn modern HPC infrastructure, most compute power is however not in the CPUs but in accelerators such as GPUs. In order to make use of this compute power, we have enabled MPI-AMRVAC to run on GPUs using OpenACC, enabling larger-scale simulations than ever before.\r\n\r\nI will discuss the advantages and challenges of OpenACC in our experience, and highlight the achieved performance improvement in MPI-AMRVAC on both Snellius and LUMI.", "recording_license": "", "do_not_record": false, "persons": [{"code": "KEEXE9", "name": "Leon Oostrum", "avatar": "https://pretalx.surf.nl/media/avatars/KEEXE9_zHmVy7e.jpg", "biography": "Leon is a research software engineer at the Netherlands eScience Center, mainly focusing on GPU acceleration. He obtained his PhD in astronomy at ASTRON and the University of Amsterdam in 2020, having worked on the software and first science of the upgraded Westerbork Radio Telescope.", "public_name": "Leon Oostrum", "guid": "2613eb02-7794-5ce3-979d-fcb9c8bf1fca", "url": "https://pretalx.surf.nl/acud-2025/speaker/KEEXE9/"}], "links": [], "feedback_url": "https://pretalx.surf.nl/acud-2025/talk/Z7DXLP/feedback/", "origin_url": "https://pretalx.surf.nl/acud-2025/talk/Z7DXLP/", "attachments": []}, {"guid": "daf09537-3760-578d-b513-8fb0dce7d8d3", "code": "YBPFRY", "id": 4412, "logo": null, "date": "2025-12-04T11:30:00+01:00", "start": "11:30", "duration": "00:25", "room": "Mission 2", "slug": "acud-2025-4412-partitionedarrays-an-alternative-programming-model-for-distributed-memory-parallel-systems", "url": "https://pretalx.surf.nl/acud-2025/talk/YBPFRY/", "title": "PartitionedArrays: an alternative programming model for distributed-memory parallel systems", "subtitle": "", "track": "High Performance Computing", "type": "Short presentation with Q&A", "language": "en", "abstract": "In this presentation, we discuss the PartitionedArrays programming model as an alternative to the message passing interface (MPI). We present the key features of this model and illustrate how it can help users of Snellius and other supercomputers to reduce the burden of implementing complex distributed-memory parallel applications. We illustrate the capabilities of this model with the implementation of key kernels in scientific computing such as the distributed sparse matrix-vector product (SpMV), the distributed sparse matrix-matrix product (SpMM), as well as the high-performance conjugate gradient (HPCG) benchmark used in the top 500 supercomputer list. We also compare the performance of the resulting codes against state-of-the art implementations, showing that the proposed model improves user experience without compromising performance, or even improving it.", "description": "MPI is the gold-standard to program distributed-memory parallel computers, but it comes with well-known challenges. The programmer explicitly controls data distribution and communication, making the logic of MPI-enabled algorithms significantly more complex than their sequential versions. Debugging this additional logic at large scales is cumbersome or even impractical. Execution order might affect results and inspecting the local variables might be very tedious and time consuming, even for a moderate number of processes. Partitioned Global Address Space (PGAS) systems and other alternatives to MPI have been introduced to address these challenges. They often aim at freeing the users from communication-related details, but they offer less control on performance and face a strong adoption barrier as the programming model of MPI is deeply rooted in the high-performance computing (HPC) community. The PartitionedArrays programming model solves the challenges of MPI without the limitations of PGAS. It provides an effective way of expressing and debugging the logic of distributed applications instead of trying to hide these details from the user. To this end, PartitionedArrays decouples the number of parts used for data partition from the number of processes that run the code. Hence, the logic of data distribution and communication can be debugged on a single process using conventional tools. Moreover, computation and communication are written as a sequence of logically collective phases, which (unlike many MPI directives) have deterministic semantics independently of process execution order. This allows one to implement safety checks and rule out the possibility of dead-locks. These additional benefits come with virtually no penalty in performance, since MPI can still be used to run algorithms implemented with PartitionedArrays by setting the number of parts equal to the number of processes. In addition, the logic of many MPI codes can be expressed in PartitionedArrays allowing to readily port applications developed with MPI in mind, minimizing its adoption barrier in the HPC community. \r\n\r\nPartitionedArrays is FAIR software available at https://github.com/PartitionedArrays/PartitionedArrays.jl", "recording_license": "", "do_not_record": false, "persons": [{"code": "XJNP9N", "name": "Francesc Verdugo", "avatar": "https://pretalx.surf.nl/media/avatars/XJNP9N_tXOYPyV.png", "biography": "Assistant Professor at VU Amsterdam Department of Computer Science.", "public_name": "Francesc Verdugo", "guid": "b0ed86e0-aa29-5f6c-b80a-9afd29172557", "url": "https://pretalx.surf.nl/acud-2025/speaker/XJNP9N/"}], "links": [], "feedback_url": "https://pretalx.surf.nl/acud-2025/talk/YBPFRY/feedback/", "origin_url": "https://pretalx.surf.nl/acud-2025/talk/YBPFRY/", "attachments": []}, {"guid": "696029eb-c4d0-514b-8727-79dc97773b95", "code": "3FS7CU", "id": 4415, "logo": null, "date": "2025-12-04T14:10:00+01:00", "start": "14:10", "duration": "00:25", "room": "Mission 2", "slug": "acud-2025-4415-real-time-quantitative-mri-reconstruction", "url": "https://pretalx.surf.nl/acud-2025/talk/3FS7CU/", "title": "Real-time Quantitative MRI Reconstruction", "subtitle": "", "track": "High Performance Computing", "type": "Short presentation with Q&A", "language": "en", "abstract": "In this talk, we address the challenges of quantitative MRI (qMRI) reconstruction and introduce COMPAS, a flexible and GPU-accelerated toolkit designed for use in qMRI research. Our evaluation shows that COMPAS significantly reduces reconstruction times, from hours to minutes, using the GPU infracture provided by SURF, including Snellius and LUMI supercomputers.", "description": "Quantitative MRI (qMRI) has great potential to transform clinical radiology by offering higher-quality medical images while reducing acquisition times. This enables faster diagnoses by radiologists and shorter scanning times for patients. However, the computational demands of qMRI algorithms are significant, often causing image reconstruction to take hours and thus hindering clinical adoption.\r\n\r\nWe present COMPAS, a composable toolkit of high-performance qMRI primitives for developing state-of-the-art qMRI methods. COMPAS hides the technical complexity required to achieve near-real-time performance while providing an easy-to-use interface for both C++ and Julia.\r\n\r\nCOMPAS integrates several cutting-edge technologies, including work developed at the Netherlands eScience Center. We use Kernel Tuner to auto-tune the performance of individual GPU kernels. We develop KMM, a parallel dataflow and memory-manager layer for multi-GPU systems that minimizes data transfers, reuses GPU allocations, and overlaps computation with communication. We also perform selected operations in low precision to increase performance at the cost of a minimal loss in numerical accuracy. Finally, by targeting both CUDA and HIP, we support AMD and NVIDIA GPUs with a single codebase.\r\n\r\nWe present results using Snellius (NVIDIA H100) and LUMI (AMD MI250X) supercomputers, reducing reconstruction times from hours to nearly one minute, making qMRI ready for potential use in clinical trials.", "recording_license": "", "do_not_record": false, "persons": [{"code": "7JAGEE", "name": "Alessio Sclocco", "avatar": "https://pretalx.surf.nl/media/avatars/7JAGEE_ObW9ntH.jpeg", "biography": "Alessio Sclocco is a research software engineer at the Netherlands eScience Center, specializing in optimizing GPU applications for scientific research. He earned his PhD in computer science from VU University Amsterdam in 2017, with a thesis titled \"Accelerating Radio Astronomy with Auto-tuning.\" Previously, he worked at ASTRON, where he developed AMBER, an optimized GPU pipeline for detecting radio astronomical transients. Since 2012, Alessio has been dedicated to fostering computational excellence through mentoring and teaching GPU programming, helping others achieve high performance in their code.", "public_name": "Alessio Sclocco", "guid": "ec467f11-6b6d-5b22-867a-031c9b8b5117", "url": "https://pretalx.surf.nl/acud-2025/speaker/7JAGEE/"}, {"code": "YRKB8K", "name": "Stijn Heldens", "avatar": "https://pretalx.surf.nl/media/avatars/YRKB8K_2X3AWBa.jpg", "biography": "Stijn is a Research Software Engineer at the Netherlands eScience Center, where he develops scalable software solutions for scientific research. His work focuses on high-performance and parallel computing.\r\n\r\nHe received his Master\u2019s degree in Computer Science from VU University Amsterdam with a specialization in High-Performance Computing. Before joining the eScience Center, Stijn worked at Delft University of Technology and the University of Twente on several graph-processing research projects. He completed his PhD at the University of Amsterdam with the dissertation Parallel Programming Systems for Scalable Scientific Computing. His research interests include parallel algorithm design, large-scale distributed and parallel data processing, and GPU programming.", "public_name": "Stijn Heldens", "guid": "fa325b06-c9f9-5109-9a33-6f82b6a248c4", "url": "https://pretalx.surf.nl/acud-2025/speaker/YRKB8K/"}, {"code": "LV8UV8", "name": "Oscar van der Heide", "avatar": null, "biography": null, "public_name": "Oscar van der Heide", "guid": "d8a34013-b9c8-5af7-ac30-321157fb0b0a", "url": "https://pretalx.surf.nl/acud-2025/speaker/LV8UV8/"}], "links": [], "feedback_url": "https://pretalx.surf.nl/acud-2025/talk/3FS7CU/feedback/", "origin_url": "https://pretalx.surf.nl/acud-2025/talk/3FS7CU/", "attachments": []}, {"guid": "fca13c66-8e5d-51cb-b19b-f5f26c8c9236", "code": "LLQ3MN", "id": 4407, "logo": null, "date": "2025-12-04T15:25:00+01:00", "start": "15:25", "duration": "00:25", "room": "Mission 2", "slug": "acud-2025-4407-preparing-for-einstein-telescope-gpu-native-scientific-computing-without-compromises", "url": "https://pretalx.surf.nl/acud-2025/talk/LLQ3MN/", "title": "Preparing for Einstein Telescope: GPU-native scientific computing without compromises", "subtitle": "", "track": "High Performance Computing", "type": "Short presentation with Q&A", "language": "en", "abstract": "Gravitational wave astronomy has advanced from theoretical prediction to observational reality, with over 200 black hole and neutron star mergers detected in the past decade. The Einstein Telescope, a proposed next-generation detector with a candidate site at the border of the Netherlands, Germany, and Belgium, is expected to detect hundreds of thousands of events per year. However, analyzing this unprecedented volume of observations poses a fundamental challenge, as existing software cannot scale to extract science from such a rich dataset. We present ongoing development of a GPU-native framework written in JAX that accelerates the analysis of gravitational wave data from hours to mere minutes. Crucially, our approach avoids using machine learning surrogates, preserving high fidelity in the results while achieving this speedup. By developing and testing our framework on the Snellius GPU cluster, we underscore the Netherlands' active role in both the instrumentation and the data analysis for the Einstein Telescope.", "description": "See abstract", "recording_license": "", "do_not_record": false, "persons": [{"code": "TJFPQP", "name": "Thibeau Wouters", "avatar": "https://pretalx.surf.nl/media/avatars/TJFPQP_UCcxPhB.jpg", "biography": "PhD candidate at Utrecht University, working on Bayesian data analysis of gravitational waves, multi-messenger astrophysics and nuclear physics. Preparing software for future experiments such as Einstein Telescope and Cosmic Explorer.", "public_name": "Thibeau Wouters", "guid": "cfee9358-7824-55c7-a80b-b5b157d28350", "url": "https://pretalx.surf.nl/acud-2025/speaker/TJFPQP/"}], "links": [], "feedback_url": "https://pretalx.surf.nl/acud-2025/talk/LLQ3MN/feedback/", "origin_url": "https://pretalx.surf.nl/acud-2025/talk/LLQ3MN/", "attachments": []}]}}]}}}