Study on Case-Based Parallel Programming for Multi-threads

我们的基于实例的并行编程研究的主要问题是，与线程和同步相比，任务划分的可重用性较低。该研究基于并行算法类对任务划分进行了详细的分类，研究了任务划分的组成部分，并通过分析每个并行算法类上开发的22个并行程序对任务划分进行了分类。除了前三类(块、循环和复制：1级)外，还提供了2级(表示简单/重复、固定/变量、划分数目等更细微的信息)和3级(表示基于2级的必要数据)，这些分类提高了案例检索的精确度，从而可以检索到更多相似的案例。此外，一种自动检测程序，其删除除程序概要之外的不必要的行，并插入显示应该描述的内容的注释。在此基础上，将16台PC机接入以太网，构建了PC机集群系统。在集群上安装了PVM，并进行了PVM并行编程实验。目前，已有8台PC连接了快速网卡、Myrnet，并通过安装集群系统软件SCORE开发了分布式共享内存环境。简单的OpenMP并行程序在4台PC机群上用Myrnet和SCORE正确执行。

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.