Modeling and Analysis of the Page Sizing Problem for NVM Storage in Virtualized Systems

Yunjoo Park, Hyokyung Bahn

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


Recently, NVM (non-volatile memory) has advanced as a fast storage medium, and traditional memory management systems designed for HDD storage should be reconsidered. In this article, we revisit the page sizing problem in NVM storage, specially focusing on virtualized systems. The page sizing problem has not caught attention in traditional systems because of the two reasons. First, the memory performance is not sensitive to the page size when HDD is adopted as storage. We show that this is not the case in NVM storage by analyzing the TLB miss rate and the page fault rate, which have trade-off relations with respect to the page size. Second, changing the page size in traditional systems is not easy as it accompanies significant overhead. However, due to the widespread adoption of virtualized systems, the page sizing problem becomes feasible for virtual machines, which are generated for executing specific workloads with fixed hardware resources. In this article, we design a page size model that accurately estimates the TLB miss rate and the page fault rate for NVM storage. We then present a method that has the ability of estimating the memory access time as the page size is varied, which can guide a suitable page size for given environments. By considering workload characteristics with given memory and storage resources, we show that the memory performance of virtualized systems can be improved by 38.4% when our model is adopted.

Original languageEnglish
Article number9391659
Pages (from-to)52839-52850
Number of pages12
JournalIEEE Access
StatePublished - 2021

Bibliographical note

Funding Information:
This work was supported in part by the National Research Foundation of Korea (NRF) Grant by the Korean Government through MSIP under Grant 2019R1A2C1009275, and in part by the ICT Research and Development Program of MSIP/IITP (Developing system software technologies for emerging new memory that adaptively learn workload characteristics) under Grant 2019-0-00074.

Publisher Copyright:
© 2013 IEEE.


  • NVM
  • Page size
  • address translation
  • memory performance
  • page fault
  • virtualization


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