MacroTrend:A Write-Efficient Cache Algorithm for NVM-Based Read Cache

• 作者: Ning Bao Yun-Peng Chai Xiao Qin Chuan-Wen Wang
• 来源期刊: 计算机科学技术学报（英文版）
• 年，卷（期）: 2022,（1）
• 所属期刊栏目: Regular Paper
• 页码范围: 207-230
• 页数: 24页
• 语种: 英文

摘要

The future storage systems are expected to contain a wide variety of storage media and layers due to the rapid development of NVM(non-volatile memory)techniques.For NVM-based read caches,many kinds of NVM devices cannot stand frequent data updates due to limited write endurance or high energy consumption of writing.However,traditional cache algorithms have to update cached blocks frequently because it is difficult for them to predict long-term popularity according to such limited information about data blocks,such as only a single value or a queue that reflects frequency or recency.In this paper,we propose a new MacroTrend(macroscopic trend)prediction method to discover long-term hot blocks through blocks'macro trends illustrated by their access count histograms.And then a new cache replacement algorithm is designed based on the MacroTrend prediction to greatly reduce the write amount while improving the hit ratio.We conduct extensive experiments driven by a series of real-world traces and find that compared with LRU,MacroTrend can reduce the write amounts of NVM cache devices significantly with similar hit ratios,leading to longer NVM lifetime or less energy consumption.