This thesis addresses the basic ideas and approaches used when parallelizing
biologically inspired algorithms. Its foundation is an attempt of speeding
up an algorithm developed on the Jožef Stefan Institute, that is based on
the stigmergy of ants. How? With the use of graphics processor and the
intended framework, OpenCL. What had to be done was to prepare a set of
the so called code kernels that will take pieces of the algorithm suited for
parallel computing, and execute them on the graphics card; optimize them
as much as possible, and perform the required measurements. The thesis
describes individual steps of the parallelized algorithm, it provides some general guidelines for the parallelization of biologically inspired algorithm and
presents the actual measurement results. The latter are presented in different contexts (comparison of individual algorithm steps execution times with
respect to the used number of threads, comparison of individual algorithm
steps parallel execution time with the individual steps sequential execution
time, and comparison of the total parallel algorithm execution time with the
total sequential algorithm execution time).
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