Towards High Performance and Efficient Memory Deduplication via Mixed Pages

Abstract

Large pages are widely supported in modern hardware and OSes to reduce the overhead of TLB misses. However, memory deduplication can be inefficient with large pages, leading to low memory utilization. To simultaneously enjoy the benefits of high performance by accessing memory with large pages (e.g., 2 MB pages) and high deduplication rate by managing memory with base pages (e.g., 4 KB pages), we propose <u>Smart</u> <u>M</u> emory <u>D</u> eduplciation (SmartMD), which is an adaptive and efficient memory management scheme via mixed pages. Specifically, we propose lightweight schemes to periodically monitor pages’ access frequency and repetition rate, and present an adaptive conversion scheme to selectively split or reconstruct large pages. We further optimize SmartMD by developing SmartMD <inline-formula><tex-math notation="LaTeX">$^{+}$</tex-math></inline-formula> , which dynamically adjusts the page scanning cycle by monitoring the TLB miss cost, and reconstructs the split large pages in an on-demand way so as to reduce the CPU overhead of SmartMD. We further implement a prototype system and conduct extensive experiments with various workloads under different system settings. Experiment results show that SmartMD and SmartMD <inline-formula><tex-math notation="LaTeX">$^{+}$</tex-math></inline-formula> can simultaneously achieve high access performance similar to systems using large pages, and achieve a deduplication rate similar to that applying aggressive deduplication scheme (i.e., KSM) on base pages.