From Exascale Supercomputing to FAIR data
I am giving a talk on the H2020 projects DEEP-EST and EOSC-Nordic (including EUDAT's B2FIND and B2SHARE) at the University of Iceland's Engineering Research Institute seminar: From Exascale Supercomputing to FAIR data -- or: Why (almost) everyone uses GPUs and how to get a DOI for your dataset.
For zoom link, have a look at the official announcement.
The slide are available via DOI:10.23728/b2share.a6a4682fe1f74b32b8b67948f7ce6965
and a video recording of the presentation is available as well.
Update: The Top 500 list of the fastest supercomputer shows that the Flop/s growth is since 2013 not exponentially anymore, but is already slowing down. While Moore's low was about the number of transistors of cost optimised systems and not about Floating Point Operations per Second of Supercomputing systems, both are nevertheless related to each other and show that Moore's law is slowly coming to an end.