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Boosting performance of I/O-intensive workload by preemptive job migrations in a cluster system

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4 Author(s)
Xiao Qin ; Dept. of Comput. Sci. & Eng., Univ. of Nebraska-Lincoln, Lincoln, NE, USA ; Hong Jiang ; Yifeng Zhu ; Swanson, D.R.

Load balancing in a cluster system has been investigated extensively, mainly focusing on the effective usage of global CPU and memory resources. However, if a significant portion of applications running in the system is I/O-intensive, traditional load balancing policies that focus on CPU and memory usage may cause the system performance to decrease substantially. To solve this problem, a new I/O-aware load-balancing scheme with preemptive job migration is presented to sustain the high performance of a cluster with a diverse set of workload conditions. The proposed scheme dynamically detects I/O load imbalance on nodes of a cluster, and determines whether to preempt some running jobs on overloaded nodes and migrate them to other less- or under-loaded nodes. Besides balancing I/O load, the scheme takes into account both CPU and memory load sharing in clusters, thereby maintaining the same level of performance as existing schemes when I/O load is low or well balanced. Results from a trace-driven simulation show that, compared to the existing approaches that only consider I/O with nonpreemptive job migrations, the proposed schemes achieve the improvement in mean slowdown by up to a factor of 10.

Published in:

Computer Architecture and High Performance Computing, 2003. Proceedings. 15th Symposium on

Date of Conference:

10-12 Nov. 2003