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Cell["Parallel Computation in Geodesy", "Title",
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"\nWidespreading multicore machines and strong support of their effective \
utilization in popular computing systems like MATLAB and ",
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" make it possible to apply parallel algorithms employed frequently in \
solving computational tasks of geodesy without special programming knowledge. \
There are two important algorithms playing central role in computational \
geodesy being parallel by nature. \n\nThe first one is the Gauss-Jacobi \
algorithm used for solving overdetermined nonlinear systems of equations. \
Many times the square subset problems can be solved by symbolic computation \
like Groebner basis or Dixon resultant. Therefore the solution of all \
combinatorial subset can be considerably fast. However, with the increase of \
the number of equations, the number of the subtasks is increasing rapidly. If \
the size of the square subsets ",
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". Fortunately, these subtasks can be solved independently, simultaneously.\
\n\nThe second algorithm is the linear homotopy, which is a global numerical \
method to solve nonlinear systems. In this algorithm the different homotopy \
paths belonging to the different solutions of the system can be traced also \
independently.\n\nIn this study the application of parallel computing \
concerning these two algorithms to solve positioning problems via resection \
and intersection in GPSS and photogrammetry will be illustrated. Organization \
of these computations in MATLAB as well as in ",
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" is demonstrated by comparing the running times in case of different \
numerical examples. Tips and techniques to utilize hardware and software \
supports of parallelization will be presented."
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