期刊名称：International Journal of Research in Management, Science & Technology
印刷版ISSN：2321-3264
出版年度：2013
卷号：1
期号：2
出版社：Prannath Parnami Institute of Management & Technology, Hisar
摘要：Distributed memory Beowulf clusters and Grids are gaining more and more interest as low cost parallel architectures are meeting high performance computing demands. With the rise of cheap commodity cluster solutions, Distributed Memory approach has inspired many research projects and has lead to significant advances in this area. Software DSM (SDSM) systems enable the use of shared memory programming approaches in loosely coupled environments. Shared memory is appealing because it isolates the programmer from the underlying communication scheme used to maintain consistency across the distributed system. On the other hand, modern organizations depend on network-attached personal desktop and mobile computer systems. A characteristic of these systems is that they are relatively resource rich (in terms of CPU power, memory, and disk capacity) but are utilized only for a fraction of the time during a day. Even during the time they are in use, their average utilization is much less than their peak capacity. Grid computing is basically coordinated resource sharing of these existing underutilized resources. These computing systems usually support embarrassingly parallel applications which consist of many instances of the same computation with their own data. The applications are usually involved with scientific problems, which need large amounts of processing capacity over long periods of time. In this paper we have surveyed various applications which can run on DSM and Grid environments individually. Based on the analysis of these applications we propose to identify applications which can be executed in an integrated model comprising of shared memory and grid-SMIG (Shared Memory Integrated with Grid). We are in the process of architecting and designing SMIG model and the applications we select will prove useful in testing this model
关键词：Distributed Memory; Grids; Clusters; Resource Sharing and SMIG Model
