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

Abstract

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.

Keywords

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