Share-o-meter: An empirical analysis of KSM based memory sharing in virtualized systems

Abstract

Content based memory sharing in virtualized environments has proven to be a useful technique for over-commitment based placement of virtual machines. Kernel-based Virtual Machine (KVM) on Linux uses Kernel SamePage Merging (KSM) to identify and exploit sharing opportunities. In this paper, we present an analysis of page sharing across virtual machines by comparing page sharing achieved by KSM to total sharing opportunities presented by virtual machines. We study the impact of different KSM configurations, system resources, and workload characteristics on page sharing achieved by KSM. We also study the cost of sharing in terms of CPU utilization overhead from Copy-On-Write page breaks that occur on KSM shared pages. Our analysis is aimed at exploring the KSM configuration space towards obtaining desired sharing levels with minimal overheads for a given amount of system resources and workload characteristics. Our empirical analysis shows that for workloads exhibiting different memory usage patterns, different KSM configuration parameters are required to achieve maximum savings. We quantify the levels of savings and associated costs for several (individual and combinations) of workloads, exhibiting different sharing opportunities and memory usage characteristics. Further, we demonstrate the need for adaptive configuration of KSM's aggressiveness based on changes in total memory available for sharing and change in memory usage characteristics.