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성기석,박지혁 한국경영과학회 1997 한국경영과학회 학술대회논문집 Vol.- No.2
For parallel processing, the compiler partitions a loaded program into a set of tasks and makes a schedule for the tasks that will minimize parallel processing time for the loaded program. Building an optimal schedule for a given set of partitioned tasks of a program has known to be NP-complete. In this paper we introduce a GA(Genetic Algorithm)-based scheduling method in which a choromosome consists of two parts of a string which decide the number and order of tasks on each processor. An additional computation is used for feasibility constraint in the chromosome. By granularity theory, a partitioned program is categorized into coarse-grain or fine-grain types. There exist good heuristic algorithms for coarse-grain type partitioning. We suggested another GA adaptive to the coarse-grain type partitioning. The infeasibility of chromosome is overcome by the encoding and operators. The number of processors are decided while the GA find the minimum parallel processing time.
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성기석,박지혁 한국경영과학회 1998 韓國經營科學會誌 Vol.23 No.2
In the parallel processing systems, a compiler partitions a loaded program into tasks, allocates the tasks on multiple processors and schedules the tasks on each allocated processor. In this paper we suggest a Genetic Algorithm(GA) based scheduling method to find an optimal allocation and sequence of tasks on each processor. The suggested method uses a chromosome which consists of task sequence and binary string that represent the number and order of tasks on each processor respectively. Two correction algorithms are used to maintain precedency constraints of the tasks in the chromosome. This scheduling method determines the optimal number of processors within limited numbers, and then finds the optimal schedule for each processor. A result from computational experiment of the suggested method is given.