PRACEdays20 Panel Discussion: Will HPC, AI and Data Science be the same in 10 years' time?
- Serge Bogaerts (PRACE)
Scientific and industrial research is taking ownership of the revolution, started a decade ago by online enterprises such as Google and Facebook, of data-centric discovery as a complement to the simulation-centric approach traditional to the HPC community. While data processing has always been at the heart of scientific discoveries relying on large-scale instruments, the need to increase the performance of the associated data processing with extreme computing and the interdependence of accurate simulations and efficient design of experiments, has become more pressing. The advent of data science resulting from the accessibility of new huge sets of data of unprecedented detail, coming from traditional research as well as from new sources such as the Internet of Things, and the ability to extract information from these efficiently also extended the scientific communities benefitting from the use of large cyberinfrastructures with, for instance, social sciences and humanities.
This convergence of interests comes with the challenge of providing an infrastructure that is suited for this wider range of research topics, and that supports new discoveries efficiently. Architectures of exascale computers relying on computing accelerators are a key element in this evolving landscape in providing, for instance, efficient platforms for AI supported research. The challenge for the decade to come is to enable researchers to leverage value of data from the edge where a significant part of the data needs to be collected, cured and filtered, to the data centre where it can be further processed at extreme scale. This is associated with the need to train researchers to use new transverse disciplines such as AI, machine learning, and data-mining, and to provide them with tools that manage the associated data logistics and implement large scale workflows across the future computing continuum. The panel will discuss the evolution towards full blending of the traditional simulation-centric research with the new data-centric paradigms for scientific and industrial discovery and innovation, and what this will look like in 10 years from now.
- Guy Lonsdale, SCAPOS
- Maria Girone, CERN
- Mark Asch, BDEC
- Joost VandeVondele, PRACE
- Alice-Agnes Gabriel, PRACE Ada Lovelace Award Winner 2020
- Jorge Almeida, Critical Software
- Maria Perez, EuroHPC RIAG