From Exascale Supercomputing to FAIR data

According to Moore's law, the number of transistors in an integrated circuit doubles about every two years, giving us faster computers in the same pace. Latest when miniaturisation reaches atomic levels, Moore's law will be coming to an end (likely in 5 to 10 years). While we see in 2020 still an increase in number of transistors, general purpose CPU cores do not really get faster anymore. This did lead to the rise of specialised "accelerators" (such as GPUs). With current High-Performance Computing clusters being in the PetaFLOPS range, Exascale (i.e. 10^18 FLOPS=floating point instructions per second) is the next (and maybe final) sonic barrier to break. The first part of this talk will report from the DEEP-EST Exascale research project that develops a modular supercomputing architecture to provide different hardware modules each employing different accelerator technologies tailored to specific problem domains, such a simulation or machine learning. The second part of this talk will cover the European Open Science Cloud (EOSC) that gathers and provides many digital services for European researchers, such as computing or storing research data. For example, you need to store research data (or just your source code), preferably even with a DOI so that you and others can reference it? -- EOSC provides the right service! With respect to Nordic research data, the EOSC-Nordic project aims at making this data FAIR, i.e. findable, accessible, interoperable, and reusable. Maybe even you have data that is worth being made FAIR?!