Software techniques to improve virtualized I/O performance on multi-core systems

  • Authors:
  • Guangdeng Liao;Danhua Guo;Laxmi Bhuyan;Steve R King

  • Affiliations:
  • University of California, Riverside;University of California, Riverside;University of California, Riverside;Intel Corporation

  • Venue:
  • Proceedings of the 4th ACM/IEEE Symposium on Architectures for Networking and Communications Systems
  • Year:
  • 2008

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Abstract

Virtualization technology is now widely deployed on high performance networks such as 10-Gigabit Ethernet (10GE). It offers useful features like functional isolation, manageability and live migration. Unfortunately, the overhead of network I/O virtualization significantly degrades the performance of network-intensive applications. Two major factors of loss in I/O performance result from the extra driver domain to process I/O requests and the extra scheduler inside the virtual machine monitor (VMM) for scheduling domains. In this paper we first examine the negative effect of virtualization in multi-core platforms with 10GE networking. We study virtualization overhead and develop two optimizations for the VMM scheduler to improve I/O performance. The first solution uses cache-aware scheduling to reduce inter-domain communication cost. The second solution steals scheduler credits to favor I/O VCPUs in the driver domain. We also propose two optimizations to improve packet processing in the driver domain. First we re-design a simple bridge for more efficient switching of packets. Second we develop a patch to make transmit (TX) queue length in the driver domain configurable and adaptable to 10GE networks. Using all the above techniques, our experiments show that virtualized I/O bandwidth can be increased by 96%. Our optimizations also improve the efficiency by saving 36% in core utilization per gigabit. All the optimizations are based on pure software approaches and do not hinder live migration. We believe that the findings from our study will be useful to guide future VMM development.