Towards a European HPC/AI ecosystem: a community-driven report
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| Název: | Towards a European HPC/AI ecosystem: a community-driven report |
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| Autoři: | Petr Taborsky, Iacopo Colonnelli, Krzysztof Kurowski, Rakesh Sarma, Niels Henrik Pontoppidan, Branislav Jansík, Nicki Skafte Detlefsen, Jens Egholm Pedersen, Rasmus Larsen, Lars Kai Hansen |
| Zdroj: | Procedia Computer Science. 255:140-149 |
| Informace o vydavateli: | Elsevier BV, 2025. |
| Rok vydání: | 2025 |
| Témata: | Artificial Intelligence, High-Performance Computing, HPC, ELISE, ELLIS, EuroHPC Joint Undertaking, Quantum Computing, Federated Learning |
| Popis: | The rapid advancements in AI and Machine Learning necessitate a robust computational infrastructure to support cutting-edge research and industrial applications. From the academic and industrial AI community perspective, voiced in the recent ELISE project, the European AI platform is recommended to center around the EuroHPC growing ecosystem. It should be user-driven, easily accessible, powerful, and compliant with European regulations. AI-optimized and dedicated supercomputers for the European AI community are also coming, in addition to upgrading partitions of existing EuroHPC systems to ’AI enabled’ stage. Related calls have been initiated in September 2024. Further, conventional EuroHPC systems are suggested to be extended with quantum computing, edge AI, and neuromorphic computing to cater to AI models deployed on network edge devices and sustainability in the long run. The challenges are presented in three case studies, ranging from training Transformers on HPC to LLMs trained federally across three different Euro HPC systems to recent results on hybrid classical-quantum application. This paper concludes with case studies results-informed next steps believed to benefit AI practitioners and the broader AI community. |
| Druh dokumentu: | Article Conference object |
| Popis souboru: | application/pdf |
| Jazyk: | English |
| ISSN: | 1877-0509 |
| DOI: | 10.1016/j.procs.2025.02.269 |
| Přístupová URL adresa: | https://www.sciencedirect.com/science/article/pii/S1877050925006301 https://hdl.handle.net/2318/2062570 https://doi.org/10.1016/j.procs.2025.02.269 |
| Rights: | CC BY |
| Přístupové číslo: | edsair.doi.dedup.....d0c81cbc6bb5237d608303a27f91dcac |
| Databáze: | OpenAIRE |
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Nájsť tento článok vo Web of Science | Abstrakt: | The rapid advancements in AI and Machine Learning necessitate a robust computational infrastructure to support cutting-edge research and industrial applications. From the academic and industrial AI community perspective, voiced in the recent ELISE project, the European AI platform is recommended to center around the EuroHPC growing ecosystem. It should be user-driven, easily accessible, powerful, and compliant with European regulations. AI-optimized and dedicated supercomputers for the European AI community are also coming, in addition to upgrading partitions of existing EuroHPC systems to ’AI enabled’ stage. Related calls have been initiated in September 2024. Further, conventional EuroHPC systems are suggested to be extended with quantum computing, edge AI, and neuromorphic computing to cater to AI models deployed on network edge devices and sustainability in the long run. The challenges are presented in three case studies, ranging from training Transformers on HPC to LLMs trained federally across three different Euro HPC systems to recent results on hybrid classical-quantum application. This paper concludes with case studies results-informed next steps believed to benefit AI practitioners and the broader AI community. |
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| ISSN: | 18770509 |
| DOI: | 10.1016/j.procs.2025.02.269 |