On the automatic generation of efficient parallel iterative sorting algorithms

Increasing availability of multiple processing elements on the recent desktop and personal computers poses unavoidable challenges in realizing their processing power. The challenges include programming these high processing elements. Parallel programming is an apt solution for such a realization of the computational capacity. However, it has many difficulties in developing the parallel programs. We present Multi-core Grammatical Evolution for Parallel Sorting (MCGE-PS) that automatically produces native parallel sorting programs. These programs are of iterative nature that also exploit the processing power of the multicore processors efficiently. The performance of the resultant programs is measured in terms of the execution time. The results indicate a significant improvement over the state-of-the-art implementations. Finally, we conduct an empirical analysis on computational complexity of the evolving parallel programs. The results are competitive with that of the state-of-the-art evolutionary attempts.