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IEEE International Conference on Cluster Computing (CLUSTER'03)   p. 100
Towards Load Balancing Support for I/O-Intensive Parallel Jobs in a Cluster of Workstations
Xiao Qin, University of Nebraska-Lincoln
Hong Jiang, University of Nebraska-Lincoln
Yifeng Zhu, University of Nebraska-Lincoln
David R. Swanson, University of Nebraska-Lincoln

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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CLUSTR.2003.1253305
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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/Oaware 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.
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Citation:  Xiao Qin, Hong Jiang, Yifeng Zhu, David R. Swanson, "Towards Load Balancing Support for I/O-Intensive Parallel Jobs in a Cluster of Workstations," cluster, p. 100,  IEEE International Conference on Cluster Computing (CLUSTER'03),  2003