CMD: classification-based memory deduplication through page access characteristics

• Authors: Licheng Chen;Zhipeng Wei;Zehan Cui;Mingyu Chen;Haiyang Pan;Yungang Bao
• Venue: Proceedings of the 10th ACM SIGPLAN/SIGOPS international conference on Virtual execution environments
• Year: 2014

Limited main memory size is considered as one of the major bottlenecks in virtualization environments. Content-Based Page Sharing (CBPS) is an efficient memory deduplication technique to reduce server memory requirements, in which pages with same content are detected and shared into a single copy. As the widely used implementation of CBPS, Kernel Samepage Merging (KSM) maintains the whole memory pages into two global comparison trees (a stable tree and an unstable tree). To detect page sharing opportunities, each tracked page needs to be compared with pages already in these two large global trees. However since the vast majority of compared pages have different content with it, that will induce massive futility comparisons and thus heavy overhead. In this paper, we propose a lightweight page Classification-based Memory Deduplication approach named CMD to reduce futile page comparison overhead meanwhile to detect page sharing opportunities efficiently. The main innovation of CMD is that pages are grouped into different classifications based on page access characteristics. Pages with similar access characteristics are suggested to have higher possibility with same content, thus they are grouped into the same classification. In CMD, the large global comparison trees are divided into multiple small trees with dedicated local ones in each page classification. Page comparisons are performed just in the same classification, and pages from different classifications are never compared (since they probably result in futile comparisons). The experimental results show that CMD can efficiently reduce page comparisons (by about 68.5%) meanwhile detect nearly the same (by more than 98%) or even more page sharing opportunities.