{"title":"使用移动代理的分布式并行环境中的增强调度方法","authors":"M. Dantas, J. G. R. C. Lopes, T. G. Ramos","doi":"10.1109/HPCSA.2002.1019152","DOIUrl":null,"url":null,"abstract":"Our goal is to apply mobile agent technology to provide a better scheduling for MPI applications executing in a cluster configuration. This approach could represent in a distributed cluster environment an enhancement on the load balancing of the parallel processes. MPI in a cluster of heterogeneous machines could lead parallel programmers to obtain frustrated results, mainly because of the lack of an even distribution of the workload in the cluster. As a result, before submitting a MPI application to a cluster, we use our JOTA mobile agent approach to acquire a more precise information of machine's workload. Therefore, with a more precise knowledge of the load and characteristics in each machine, we are ready to gather lightweight workstations to form a cluster. Our empirical results indicate that it is possible to spend less elapsed time when considering the execution of a parallel application using the agent approach in comparison to an ordinary MPI environment.","PeriodicalId":111862,"journal":{"name":"Proceedings 16th Annual International Symposium on High Performance Computing Systems and Applications","volume":"426 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"An enhanced scheduling approach in a distributed parallel environment using mobile agents\",\"authors\":\"M. Dantas, J. G. R. C. Lopes, T. G. Ramos\",\"doi\":\"10.1109/HPCSA.2002.1019152\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Our goal is to apply mobile agent technology to provide a better scheduling for MPI applications executing in a cluster configuration. This approach could represent in a distributed cluster environment an enhancement on the load balancing of the parallel processes. MPI in a cluster of heterogeneous machines could lead parallel programmers to obtain frustrated results, mainly because of the lack of an even distribution of the workload in the cluster. As a result, before submitting a MPI application to a cluster, we use our JOTA mobile agent approach to acquire a more precise information of machine's workload. Therefore, with a more precise knowledge of the load and characteristics in each machine, we are ready to gather lightweight workstations to form a cluster. Our empirical results indicate that it is possible to spend less elapsed time when considering the execution of a parallel application using the agent approach in comparison to an ordinary MPI environment.\",\"PeriodicalId\":111862,\"journal\":{\"name\":\"Proceedings 16th Annual International Symposium on High Performance Computing Systems and Applications\",\"volume\":\"426 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-06-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings 16th Annual International Symposium on High Performance Computing Systems and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HPCSA.2002.1019152\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 16th Annual International Symposium on High Performance Computing Systems and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPCSA.2002.1019152","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An enhanced scheduling approach in a distributed parallel environment using mobile agents
Our goal is to apply mobile agent technology to provide a better scheduling for MPI applications executing in a cluster configuration. This approach could represent in a distributed cluster environment an enhancement on the load balancing of the parallel processes. MPI in a cluster of heterogeneous machines could lead parallel programmers to obtain frustrated results, mainly because of the lack of an even distribution of the workload in the cluster. As a result, before submitting a MPI application to a cluster, we use our JOTA mobile agent approach to acquire a more precise information of machine's workload. Therefore, with a more precise knowledge of the load and characteristics in each machine, we are ready to gather lightweight workstations to form a cluster. Our empirical results indicate that it is possible to spend less elapsed time when considering the execution of a parallel application using the agent approach in comparison to an ordinary MPI environment.