EU

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 671698.

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ExaHyPE - An Exascale Hyperbolic PDE Engine

Many aspects of our life, but also cutting-edge research questions, hinge on the solution of large systems of partial differential equations expressing conservation laws. Such equations are solved to compute accurate weather forecast, complex earthquake physics, hematic flows in patients, or the most catastrophic events in the universe. Yet, our ability to exploit the predictive power of these models is still severely limited by the computational costs of their solution. Thus, the simulation of earthquakes and their induced hazards is not yet accurate enough to prevent human losses. And our ability to model astrophysical objects is still insufficient to explain our observations.

While exascale supercomputers promise the performance to tackle such problems, current numerical methods are either too expensive, because not sufficiently accurate, or too inefficient, because unable to exploit the latest supercomputing hardware. Exascale software needs to be redesigned to meet the disruptive hardware changes caused by severe constraints in energy consumption.

Research Partners

1_tum 2_udsdt 3_durham 4_fias 5_lmu 6_rsc 7_bayfor 8_lrz
EU

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 671698.