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Parallelization and virtualization of genetic algorithms for sorting permutations by reversals

机译:遗传算法的并行化与虚拟化,用于逆转排序排列

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Reversals are operations of great biological significance for the analysis of the evolutionary distance between organisms. Genome rearrangement through reversals, consists in finding the shortest sequence of reversals to transform one genome represented as a signed or unsigned permutation into another. When genes are non oriented and correspondingly permutations are unsigned, sorting by reversals came arise as a challenging problem in combinatorics of permutations. In fact, this problem is known to be NP-hard, but the question whether it is NP-complete remains open for more than twenty years. When permutations are signed and correspondingly genes are oriented, the problem is known to be in P. A parallelization of a standard GA (Genetic Algorithm) is proposed for the problem of sorting unsigned permutations. This GA was previously reported in the literature as the most competitive regarding precision for which as control mechanism an 1.5-approximation algorithm was used. For the parallelization, the MPI Library of the C language was used and experiments were performed for calculating the execution time and precision. By increasing the number of individuals, experiment showed improvement in relation to previous approaches. Additionally, a virtualization of the GA using a MicroBlaze processor from Xilinx was performed on OVP for which the average number of executed instructions was of approximately 1.40 Giga instruction per second.
机译:逆转是对生物之间的进化距离分析的巨大生物学意义的作用。基因组通过逆转重新排列,包括找到最短的逆转序列,将一个基因组转化为签名或无符号排列的一个基因组。当基因是非定向的,相应的置换是无符号的,逆转分类是由于置换的组合学中的一个具有挑战性的问题。事实上,这个问题已知是NP - 艰难的,但是问题是NP-Treate是否仍然开放二十年。当签署释义并相应的基因取向时,已知问题在于P.标准GA(遗传算法)的并行化被提出用于排序无符号置换的问题。该GA先前在文献中报告为最具竞争力的精确度,因为使用了控制机制1.5近似算法。对于并行化,使用C语言的MPI库并进行实验,用于计算执行时间和精度。通过增加个人数量,实验表明与先前的方法有关。另外,在OVP上执行使用来自Xilinx的微孔处理器的Ga的虚拟化,其执行的指令的平均数量为每秒大约1.40 giga指令。

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