MaxMem: Colocation and Performance for Big Data Applications on Tiered Main Memory Servers

Amanda Raybuck, Wei Zhang, Kayvan Mansoorshahi, Aditya K. Kamath,Mattan Erez,Simon Peter

CoRR(2023)

引用 0|浏览2
暂无评分
摘要
We present MaxMem, a tiered main memory management system that aims to maximize Big Data application colocation and performance. MaxMem uses an application-agnostic and lightweight memory occupancy control mechanism based on fast memory miss ratios to provide application QoS under increasing colocation. By relying on memory access sampling and binning to quickly identify per-process memory heat gradients, MaxMem maximizes performance for many applications sharing tiered main memory simultaneously. MaxMem is designed as a user-space memory manager to be easily modifiable and extensible, without complex kernel code development. On a system with tiered main memory consisting of DRAM and Intel Optane persistent memory modules, our evaluation confirms that MaxMem provides 11% and 38% better throughput and up to 80% and an order of magnitude lower 99th percentile latency than HeMem and Linux AutoNUMA, respectively, with a Big Data key-value store in dynamic colocation scenarios.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要