{"title":"提高在集群上执行通信密集型并行应用程序的性能","authors":"X. Qin, Hong Jiang","doi":"10.1109/CLUSTR.2004.1392658","DOIUrl":null,"url":null,"abstract":"Summary form only given. Clusters have emerged as a primary and cost-effective infrastructure for parallel applications, including communication-intensive applications that transfer a large amount of data among nodes of a cluster via the interconnection network. Conventional load balancers have been proven effective in increasing the utilization of CPU, memory, and disk I/O resources in a cluster. However, most of the existing load balancing schemes ignore network resources, leaving open the opportunity for significant performance bottleneck to form for communication-intensive parallel applications due to unevenly distributed communication load. To remedy this problem, we propose a communication-aware load balancing technique that is capable of improving the performance of communication-intensive applications by increasing the effective utilization of network resources in clusters. To facilitate the proposed load-balancing scheme, we introduce a behavior model for parallel applications with large requirements of CPU, memory, network, and disk 170 resources. The proposed load-balancing scheme can make full use of this model to quickly and accurately determine the load induced by a variety of parallel applications. Simulation results on executing a diverse set of both synthetic bulk synchronous and real parallel applications on a cluster show that the proposed scheme can significantly improve the performance both in slowdown and turn-around time over three existing schemes by up to 206% (with an average of 74%) and 235% (with an average of 82%), respectively.","PeriodicalId":123512,"journal":{"name":"2004 IEEE International Conference on Cluster Computing (IEEE Cat. No.04EX935)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Improving the performance of communication-intensive parallel applications executing on clusters\",\"authors\":\"X. Qin, Hong Jiang\",\"doi\":\"10.1109/CLUSTR.2004.1392658\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Summary form only given. Clusters have emerged as a primary and cost-effective infrastructure for parallel applications, including communication-intensive applications that transfer a large amount of data among nodes of a cluster via the interconnection network. Conventional load balancers have been proven effective in increasing the utilization of CPU, memory, and disk I/O resources in a cluster. However, most of the existing load balancing schemes ignore network resources, leaving open the opportunity for significant performance bottleneck to form for communication-intensive parallel applications due to unevenly distributed communication load. To remedy this problem, we propose a communication-aware load balancing technique that is capable of improving the performance of communication-intensive applications by increasing the effective utilization of network resources in clusters. To facilitate the proposed load-balancing scheme, we introduce a behavior model for parallel applications with large requirements of CPU, memory, network, and disk 170 resources. The proposed load-balancing scheme can make full use of this model to quickly and accurately determine the load induced by a variety of parallel applications. Simulation results on executing a diverse set of both synthetic bulk synchronous and real parallel applications on a cluster show that the proposed scheme can significantly improve the performance both in slowdown and turn-around time over three existing schemes by up to 206% (with an average of 74%) and 235% (with an average of 82%), respectively.\",\"PeriodicalId\":123512,\"journal\":{\"name\":\"2004 IEEE International Conference on Cluster Computing (IEEE Cat. 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Improving the performance of communication-intensive parallel applications executing on clusters
Summary form only given. Clusters have emerged as a primary and cost-effective infrastructure for parallel applications, including communication-intensive applications that transfer a large amount of data among nodes of a cluster via the interconnection network. Conventional load balancers have been proven effective in increasing the utilization of CPU, memory, and disk I/O resources in a cluster. However, most of the existing load balancing schemes ignore network resources, leaving open the opportunity for significant performance bottleneck to form for communication-intensive parallel applications due to unevenly distributed communication load. To remedy this problem, we propose a communication-aware load balancing technique that is capable of improving the performance of communication-intensive applications by increasing the effective utilization of network resources in clusters. To facilitate the proposed load-balancing scheme, we introduce a behavior model for parallel applications with large requirements of CPU, memory, network, and disk 170 resources. The proposed load-balancing scheme can make full use of this model to quickly and accurately determine the load induced by a variety of parallel applications. Simulation results on executing a diverse set of both synthetic bulk synchronous and real parallel applications on a cluster show that the proposed scheme can significantly improve the performance both in slowdown and turn-around time over three existing schemes by up to 206% (with an average of 74%) and 235% (with an average of 82%), respectively.