Department of Informatics
نویسندگان
چکیده
In order to simulate tsunamis, the Chair of Scientific Computing of the TUM developed the Shallow Water Equations Teaching Code, which uses an augmented Riemann solver, amongst others. A characteristic of the augmented Riemann solver is its varying processing time, which depends on its input parameters like the water height or the bathymetry. Due to this variation, when the simulation is calculated on a multi-core or multi-processor system, the cells of the simulation domain can not just be divided into equal parts, each of which is assigned to a thread. Instead, a more sophisticated dynamic load balancing strategy has to be applied in order to achieve a good utilization of the processors and thus a low overall processing time of the simulation. In this thesis, several of these load balancing approaches are introduced and compared to find out which one fits the augmented Riemann solver best. The best load balancing strategy achieved a super linear speedup with 2 and 4 processors, an almost linear speedup with 8 processors and an about 20 percent better speedup with 16 processors than the no-load-balancing version.
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