Boosting Data Center Performance via Intelligently Managed Multi-backend Disaggregated Memory

Jing Wang, Hanzhang Yang, Chao Li, Yiming Zhuansun, Wang Yuan, Cheng Xu, Xiaofeng Hou, Minyi Guo, Yang Hu, Yaqian Zhao

Abstract: Existing disaggregated memory (DM) systems face a problem of underutilized far memory bandwidth, which greatly limits the data throughput when processing data-intensive applications. Specifically, prior works all target runtime design for a single PCIe-based secondary memory device (i.e., single-backend far memory) with low data bandwidth and high system overhead.In this work, we take the first step to realize a well-crafted, multi-backend DM system with scale-out far memory paths. We propose xDM, a novel DM management scheme that can dynamically build and implicitly select appropriate far memory access paths. As part of xDM, we devise a smart far memory configuration strategy that can further optimize bandwidth usage effectiveness by tuning a wide set of key parameters based on synthesized information of application page data. Our design shows up to 3.9× data swap performance speedup, 2.8× data throughput increase, and 5.1× data center task throughput improvement compared with state-of-the-art works.