Education and cooperation

The advent of ExaScale computing marks a fundamental paradigm shift in science and technology. Achieving efficient Exascale computing is a matter that goes far beyond the research community. Capitalizing on ExaScale computing requires a rich, vibrant, and creative eco-system out of which the future innovative and potentially disruptive use of ExaScale can be developed.

The universality of high end computing within all branches of computational science and engineering poses a new challenge to education.
Currently, the training of scientists and engineers has deficits in teaching the knowledge that is necessary to exploit the opportunities created by ExaScale computing.

In the near future, the importance of computational methods will increase dramatically. ExaScale systems will be able to devise computational models for phenomena and processes of unprecedented complexity. Simulation based techniques will be the key to analyse and answer research problems in all fields of science, and they will be the primary tool to predict and control and thus help to design better products and to enable a sustainable development.

Only scientists and engineers who are trained to use these methods effectively, will be able to exploit this potential.

The situation in ExaScale computing is characterized simultaneously by a constellation of unequalled opportunities and a high risk of failure. With a vigorous technology race ongoing, Europe is in danger of falling behind.

A careful in-depth analysis reveals that the essential bottlenecks are not only in securing sufficient funding levels for installing and operating ExaScale systems.  Europe is still in a leading position in training and educating scientists and engineers. However, at this time, only hesitant first steps have been taken towards adopting HPC as a key technology. At this time, university education in Europe is not well positioned to address Exascale challenge.

Obstacles are the traditional disciplinary boundaries, since using ExaScale computing requires a deeper synergistic collaboration across several disciplines in engineering, science, mathematics, and computer technology.

There is a need to define a new kind of scientist  trained in more than a single one of the classical disciplines.

There is a need to develop the educational profile of “computational scientists” or “computational engineers”.

For this, the core competences out of several contributing fields must be combined, plus a sufficiently deep specialization so that these new scientists can work at the leading edge of research.