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Advent of recent high-throughput next generation sequencing technologies has fostered the demand of high performance sequence data analysis. Next generation sequence analysis is a very important but very challenging task in bioinformatics due to extremely large-scale datasets. A variety of searching methods have been proposed. Recent emerging multi-core computing technology makes it possible to speed up sequence analysis. In this paper, we discuss the problem of parallelizing next generation sequence analysis queries on multi-core technology. We develop a systematic method to solve this problem by using genetic algorithms. The proposed method provides us a globally optimal solution of this parallelization problem. The resulting efficiency and accuracy is superior to the ones obtained by using those approaches in which this problem is divided into the two parts: location and allocation, respectively.