SC2024Top-tier venue
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 data swap performance speedup, data throughput increase, and data center task throughput improvement compared with state-of-the-art works.
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Install the CLIlune papers get 8bf8cd0b-7c69-48d6-b280-0eb1eb8a6eeeCited by top-tier papers2
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