Study on Case-Based Parallel Programming for Multi-threads

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The major problem of our prevoius case-based parallel programming research was that the reusability of task division was low compared to threads and synchronization. In this research, task division was classified in detail based on parallel algorithm classes, and components of task division was investigated.Task division was classified by analysing 22 parallel programs developed for cases at every parallel algorithm class. In addition to previous three classes (block, cyclic and copy : level 1), level 2 which shows more minute information such as simple/duplicate, fixed/variable, and the number of division, as well as level 3 which shows necessary data based on level 2 were provided.The precision of case retreival increased so that more similar cases could be retrieved by introducing these classifications. Moreover, an automatic detection program that deletes unnecessary lines except program skelteons, and inserts comments which show what should be described. Consequently, the labor of case adaptation greatly reduced.Futhermore, a PC cluster was developed by connecting 16 PCs with ethernet. PVM was installed on the cluster and an experiment of PVM parallel programming was tested. At present, 8 PCs are connected with fast network cards, Myrinet, and distributed shared memory environment is developed by installing cluster system software SCore. Simple OpenMP parallel programs were executed correctly on the 4 PC cluster with Myrinet and SCore.