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.
Taborsky et al. (Wed,) studied this question.