Towards Load Balancing Support for I/O-Intensive Parallel Jobs in a Cluster of Workstations. Xiao Qin, Hong Jiang, Yifeng Zhu, and David R. Swanson. In Proceedings of the 5th IEEE International Conference on Cluster Computing (Cluster 2003), Hong Kong, Dec. 1-4, 2003.
Abstract
While previous CPU- or memory-centric load balancing schemes are capable of achieving the effective usage of global CPU and memory resources in a cluster system, the cluster exhibits significant performance drop under I/O-intensive workload conditions due to the imbalance of I/O load. To tackle this problem, we have developed two simple yet effective I/O-aware load-balancing schemes, which make it possible to balance I/O load by assigning I/O intensive sequential and parallel jobs to nodes with light I/O loads. Moreover, the proposed schemes judiciously take into account both CPU and memory load sharing in the cluster, thereby maintaining a high performance for a wide spectrum of workload. Using a set of real I/O-intensive parallel applications in addition to synthetic parallel jobs, we show that the proposed schemes consistently outperform the existing non-I/O-aware load-balancing schemes for a diverse set of workload conditions. Importantly, the performance improvement becomes much more pronounced when the applications are I/O-intensive.
BibTeX Entry
	@inproceedings{yzhu:cluster03b, author = {Xiao Qin and Hong Jiang and Yifeng Zhu and David Swanson}, title = {Towards Load Balancing Support for {I/O}-Intensive Parallel Jobs in a Cluster of Workstations}, booktitle = {Proceedings of {IEEE} International Conference on Cluster Computing}, month = dec, year = {2003}, address = {Hong Kong} }
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Last modified on October 16, 2003