Engineering simulations are inter-disciplinary and have multiple scales, leading to a growing requirement for supercomputing resources. Solving challenges of using Peta or Exascale resources requires to...

At Exascale high-resolution, Climate and Earth system models will be feasible to better simulate the evolution and the interactions among the different complex physical and biological processes controlling natural phenomena...

The fields of physics and chemistry span a diversity of demanding computational disciplines that share a lot in terms of models and computing kernels, such as nano-physics, solid state physics, computational fluid dynamics...

Modern life science and medical research is characterized by the need to perform computations on very large data sets. Such computations cover a large number of different application areas and use a large variety of different algorithms and software...

An important pre-condition for the definition of an Exascale strategy in Europe is a clear view on the assets of present vendor HPC research activities worldwide. This in-depth knowledge will enable us to identify gaps, risks...

The three key characteristics of Exascale system architectures will influence the development of the software eco-system. The scientific community envisions impact on: OS, runtime environments, I/O systems, system management, programming models and languages...

There are many challenges in the domain of the working group on numerical libraries, solvers and algorithms. Some arise directly because of the new architectural features in Exascale computers aUDEd others arise because of the...

The core software technologies of today are ill-equipped to handle peta and Exascale systems. One of the major difficulties will be to manage massively parallel systems, composed of millions of heterogeneous cores. The challenge is particularly severe for ...