Abstract
Commodity servers deployed in the data centers are now typically using the Non-Uniform Memory Access (NUMA) architecture. The NUMA multicore servers provide scalable system performance and cost-effective property. However, virtual machines (VMs) running on NUMA systems will access remote memory and contend for shared on-chip resources, which will decrease the overall performance of VMs and reduce the efficiency, fairness, and QoS that a virtualized system is capable to provide. In this paper, we propose a “Best NUMA Node” based virtual machine scheduling algorithm and implement it in a user-level scheduler that can periodically adjust the placement of VMs running on NUMA systems. Experimental results show that our NUMA-aware virtual machine scheduling algorithm is able to improve VM performance by up to 23.4% compared with the default CFS (Completely Fair Scheduler) scheduler used in KVM. Moreover, the algorithm achieves more stable virtual machine performance.
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Cheng, Y., Chen, W., Chen, X., Xu, B., Zhang, S. (2013). A User-Level NUMA-Aware Scheduler for Optimizing Virtual Machine Performance. In: Wu, C., Cohen, A. (eds) Advanced Parallel Processing Technologies. APPT 2013. Lecture Notes in Computer Science, vol 8299. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-45293-2_3
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DOI: https://doi.org/10.1007/978-3-642-45293-2_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-45292-5
Online ISBN: 978-3-642-45293-2
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