A Linear Clustering Method for the Scheduling of the Directed Acyclic Graph Model with Multiprocessors Using Genetic Algorithm

다중프로세서를 갖는 유방향무환그래프 모델의 스케쥴링을 위한 유전알고리즘을 이용한 선형 클러스터링 해법

The scheduling of parallel computing systems consists of two procedures, the assignment of tasks to each available processor and the ordering of tasks in each processor. The assignment procedure is same with a clustering. The clustering is classified into linear or nonlinear according to the precedence relationship of the tasks in each cluster. The parallel computing system can be modeled with a Directed Acyclic Graph(DAG). By the granularity theory, DAG is categorized into Coarse Grain Type(CDAG) and Fine Grain Type(FDAG). We suggest the linear clustering method for the scheduling of CDAG using the genetic algorithm. The method utilizes a properly that the optimal schedule of a CDAG is one of linear clustering. We present the computational comparisons between the suggested method for CDAG and an existing method for the general DAG including CDAG and FDAG.