{'fraction_non_alphanumeric': 0.01694915254237288, 'fraction_numerical': 0.0, 'mean_word_length': 5.312977099236641, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Parallel loop scheduling using an evolutionary algorithm

Many computational programs use nested loops. Programs run faster if they can execute loops in parallel. Therefore nested loops parallelization is an important problem for increasing of speed-up of program executions. One of underlying stages in parallelization is scheduling tiled space for iterating nested loops. As the problem is a NP-Hard one, using traditional search methods for solving such programs does not fit the case. As a result, heuristic algorithms are suggested for dealing with the problems in question. In this paper, a revolutionary approach, base on bipartite chromosomes is developed. Practical results show that our solution approach which is inspired by heuristics provides better solutions than various alternative solutions in the literature.