Applications Know Best: Performance-Driven Memory Overcommit with Ginkgo Conference Paper uri icon

abstract

  • Memory overcommitment enables cloud providers to host more virtual machines on a single physical server, exploiting spare CPU and I/O capacity when physical memory becomes the bottleneck for virtual machine deployment. However, overcommiting memory can also cause noticeable application performance degradation. We present Ginkgo, a policy frame-work for overcomitting memory in an informed and automated fashion. By directly correlating application-level performance to memory, Ginkgo automates the redistribution of scarce memory across all virtual machines, satisfying performance and capacity constraints. Ginkgo also achieves memory gains for traditionally fixed-size Java applications by coordinating the redistribution of available memory with the activities of the Java Virtual Machine heap. When compared to a non-overcommited system, Ginkgo runs the DayTrader 2.0 and SPECWeb 2009 benchmarks with the same number of virtual machines while saving up to 73% (50% omitting free space) of a physical server's memory while keeping application performance degradation within 7%. 2011 IEEE.

name of conference

  • 2011 IEEE 3rd International Conference on Cloud Computing Technology and Science (CloudCom)

published proceedings

  • 2011 IEEE Third International Conference on Cloud Computing Technology and Science

author list (cited authors)

  • Hines, M. R., Gordon, A., Silva, M., Da Silva, D., Ryu, K., & Ben-Yehuda, M.

citation count

  • 48

complete list of authors

  • Hines, Michael R||Gordon, Abel||Silva, Marcio||Da Silva, Dilma||Ryu, Kyung||Ben-Yehuda, Muli

publication date

  • November 2011

publisher