Implementation of genetic algorithm on multi-core architectures with parallel programming

In this thesis, it is aimed to show the increase in speed-up of multi-core PCs, which are widely used even in the daily used computers thanks to rapid technological developments by parallel programming techniques. Today, multi-core architectures are used even in cell phones. However, avaliable software and hardware intrastracture does not use this opportunies. Software still run on single thread but a life cycle can run on multiple threads due to the fact that operating systems allocate different threads to the running process. Thus naturally multiple software threads can run on multiple threads but each are by a single thread at a time. In this thesis, an application independent of operating system and based on the use off all avaliable cores in the computer by using genetic algorithms, one of the optimization algorithms, has been developed. In the end of our study, a remarkable speed-up by parallel programming even on a ordinary computer has been observed. KEYWORDS : Genetic algorithm, parallel programming, multi-core