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- W135648460 abstract "This thesis presents the implementation of parallel versions of the evolFIR algorithm for SMP systems and clusters. EvolFIR is used to find optimized decompositions of FIR filters and FIR filter structures with the help of derivation tree based genetic programming. As this task is time-consuming (e.g. the decomposition of a real world FIR filter containing 595 components needs more than 14 hours to complete), the algorithm is parallelized to reduce the runtime. The first approach to be introduced is using threads on a SMP system. As the sequential evolFIR algorithm could not be parallelized with threads, a cellular version is presented that is highly parallelizable. However, the results for this approach show that nearly no speedup can be gained due to limitations of the implementation of evolFIR. The speedup for 2 CPUs accounts for 1.1 to 1.48, 4 CPUs achieve only 1.3 to 1.89 and 8 CPUs deliver a speedup of 1.38 to 1.93. This concludes that a threaded version of evolFIR is not advisable for the current code base. The second approach that is discussed uses distributed processes which communicate with the help of MPI. Every process computes a fraction of the panmictic population size. Occasionally individuals are exchanged in order to increase the diversity of the single populations. The results regarding this attempt are impressive. Depending on the polynomial class, for 2 CPUs the speedup ranges from 1.87 to 1.92, 4 CPUs show a speedup between 3.63 and 3.85 and 8 CPUs achieve a speedup of 7.28 to 7.8. All speedups are achieved while providing at least the solution quality of the sequential algorithm." @default.
- W135648460 created "2016-06-24" @default.
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- W135648460 date "2006-01-01" @default.
- W135648460 modified "2023-09-23" @default.
- W135648460 title "Parallelization of the Generation of Redundancy R educed FIR Filter Structures" @default.
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