HPC computer facilities heading towards exascale computers within a 5 year time-frame prepare the extreme parallelism with heterogeneous architectures, comprising a moderate amount of “fat” nodes and a large number of thinner nodes comprised of co-processors for the next generation of HPC hardware. Today a large proportion of research is done on teraflop class personal computers and systems, and tomorrow such departmental systems will reach petaflop scale they will then use co-processors which will be quite different from those available today research will greatly benefit by making the codes capable of using this extreme parallelism Two major factors speak in favour of an increased attention devoted to the parallel capacity of a given application: It is therefore important for scientists, and in particular scientists involved in code development, to master the tools and concepts necessary to evolving their code for these new architectures. In recent years, a trend towards using co-processors to speed-up scientific applications has become main stream. Still, the optimal use of current and future technologies will require to aggregate knowledge between physics and chemistry, algorithms design and computer sciences. The researchers in the field play a major role in this quest for performance, by continuously developing new algorithms and programming concepts taking advantage of the power of current technology. This has made possible new insights into complex phenomena and lead to many relevant discoveries. Systems of growing size and complexity can be modeled on longer time scales, thus allowing for the simulation of more and more realistic molecular systems. High Performance Computing (HPC) simulations have now been for many years a driving force for atomistic based materials simulation.
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