Revisiting Persistent Indexing Structures on Intel Optane DC Persistent Memory

• 作者: Heng Bu Ming-Kai Dong Ji-Fei Yi Bin-Yu Zang Hai-Bo Chen
• 来源期刊: 计算机科学技术学报（英文版）
• 年，卷（期）: 2021,（1）
• 所属期刊栏目: Computer Architecture and Systems
• 页码范围: 140-157
• 页数: 18页
• 语种: 英文

摘要

Persistent indexing structures are proposed in response to emerging non-volatile memory(NVM)to provide high performance yet durable indexes.However,due to the lack of real NVM hardware,many prior persistent indexing structures were evaluated via emulation,which varies a lot across different setups and differs from the real deployment.Recently,Intel has released its Optane DC Persistent Memory Module(PMM),which is the first production-ready NVM.In this paper,we revisit popular persistent indexing structures on PMM and conduct comprehensive evaluations to study the performance differences among persistent indexing structures,including persistent hash tables and persistent trees.According to the evaluation results,we find that Cacheline-Conscious Extendible Hashing(CCEH)achieves the best performance among all evaluated persistent hash tables,and Failure-Atomic ShifT B+-Tree(FAST)and Write Optimal Radix Tree(WORT)perform better than other trees.Besides,we find that the insertion performance of hash tables is heavily influenced by data locality,while the insertion latency of trees is dominated by the flush instructions.We also uncover that no existing emulation methods accurately simulate PMM for all the studied data structures.Finally,we provide three suggestions on how to fully utilize PMM for better performance,including using clflushopt/clwb with sfence instead of clflush,flushing continuous data in a batch,and avoiding data access immediately after it is flushed to PMM.