The fields of oceanography and climate simulations in general strongly rely on information technology. High performance computing provides the hard and software needed to process complex climate computations. An employee of the work group Scientific Computing of the University of Hamburg implemented an application that does a post-processing using input data from a simulation of global ocean tides. The post-processing gains further insight on that data by performing complex calculations. It uses large NetCDF input files to execute a demanding harmonic analysis and to finally produce visualizable output. It is to be analyzed and evaluated for its suitability of use on a cluster computer. This is achieved by examining the program with tracing tools and finding routines that exhibit great potential of parallel execution. Also an initial estimate regarding the program's maximum speed-up is determined by applying Amdahl's law. Further, a parallelization approach has to be chosen and implemented. The results are analyzed and compared to prior expectations and evaluations. It turns out that by implementing a hybrid parallelization that speeds up calculations and input/output using OpenMP and MPI, a speed-up of 13.0 in comparison to the original serial program can be achieved on the cluster computer of the work group Scientific Computing. Finally, possible issues that result from this thesis are highlighted as future work. The mathematical background found in the appendix, discusses and differentiates the terms harmonic analysis and Fourier analysis that are strongly related to this thesis.

@misc{OAPOTPOATS14,
	author	 = {Dominik Rupp},
	title	 = {{Optimization and parallelization of the post-processing of a tidal simulation}},
	advisors	 = {Petra Nerge and Michael Kuhn},
	year	 = {2014},
	month	 = {04},
	school	 = {Universität Hamburg},
	type	 = {Bachelor's Thesis},
	abstract	 = {The fields of oceanography and climate simulations in general strongly rely on information technology. High performance computing provides the hard and software needed to process complex climate computations. An employee of the work group Scientific Computing of the University of Hamburg implemented an application that does a post-processing using input data from a simulation of global ocean tides. The post-processing gains further insight on that data by performing complex calculations. It uses large NetCDF input files to execute a demanding harmonic analysis and to finally produce visualizable output. It is to be analyzed and evaluated for its suitability of use on a cluster computer. This is achieved by examining the program with tracing tools and finding routines that exhibit great potential of parallel execution. Also an initial estimate regarding the program's maximum speed-up is determined by applying Amdahl's law. Further, a parallelization approach has to be chosen and implemented. The results are analyzed and compared to prior expectations and evaluations. It turns out that by implementing a hybrid parallelization that speeds up calculations and input/output using OpenMP and MPI, a speed-up of 13.0 in comparison to the original serial program can be achieved on the cluster computer of the work group Scientific Computing. Finally, possible issues that result from this thesis are highlighted as future work. The mathematical background found in the appendix, discusses and differentiates the terms harmonic analysis and Fourier analysis that are strongly related to this thesis.},
}