中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 计算技术研究所
  3. 中国科学院计算技术研究所
  4. 中国科学院计算技术研究所期刊论文
  5. 英文
LB+-Trees: Optimizing Persistent Index Performance on 3DXPoint Memory

文献类型：期刊论文

作者Liu, Jihang1,2; Chen, Shimin1,2; Wang, Lujun3
刊名PROCEEDINGS OF THE VLDB ENDOWMENT
出版日期2020-03-01
卷号13期号:7页码:1078-1090
ISSN号2150-8097
DOI10.14778/3384345.3384355
英文摘要3DXPoint memory is the first commercially available NVM solution targeting mainstream computer systems. While 3DXPoint conforms to many assumptions about NVM in previous studies, we observe a number of distinctive features of 3DXPoint. For example, the number of modified words in a cache line does not affect the performance of 3DXPoint writes. This enables a new type of optimization: performing more NVM word writes per line in order to reduce the number of NVM line writes. We propose LB+-Tree, a persistent B+-Tree index optimized for 3DXPoint memory. LB+-Tree nodes are 256B or a multiple of 256B, as 256B is the internal data access size in 3DXPoint memory. We propose three techniques to improve LB+-Tree's insertion performance: (i) Entry moving, which reduces the number of NVM line writes for insertions by creating empty slots in the first line of a leaf node; (ii) Logless node split, which uses NAW (NVM Atomic Write) to reduce logging overhead; and (iii) Distributed headers, which makes (i) and (ii) effective for multi-256B nodes. Theoretical analysis shows that entry moving reduces the number of NVM line writes per insertion of the traditional design by at least 1.35x in a stable tree. Our micro-benchmark experiments on a real machine equipped with 3DXPoint memory shows that LB+-Tree achieves up to 1.12-2.92x speedups over state-of-the-art NVM optimized B+-Trees for insertions while obtaining similar search and deletion performance. Moreover, we study the benefits of LB+-Tree in two real-world systems: X-Engine, a commercial OLTP storage engine, and Memcached, an open source key-value store. X-Engine and Memcached results confirm our findings in the micro-benchmarks.
资助项目National Key R&D Program of China[2018YEB1003303] ; NSFC[61572468] ; Alibaba collaboration project[XT622018000648] ; K.C.Wong Education Foundation
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000573956000010
出版者ASSOC COMPUTING MACHINERY
源URL[http://119.78.100.204/handle/2XEOYT63/15634]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Liu, Jihang
作者单位1.Chinese Acad Sci, ICT, SKL Comp Architecture, Beijing, Peoples R China
2.Univ Chinese Acad Sci, Beijing, Peoples R China
3.Alibaba Grp, Hangzhou, Zhejiang, Peoples R China
推荐引用方式
GB/T 7714		 Liu, Jihang,Chen, Shimin,Wang, Lujun. LB+-Trees: Optimizing Persistent Index Performance on 3DXPoint Memory[J]. PROCEEDINGS OF THE VLDB ENDOWMENT,2020,13(7):1078-1090.
APA Liu, Jihang,Chen, Shimin,&Wang, Lujun.(2020).LB+-Trees: Optimizing Persistent Index Performance on 3DXPoint Memory.PROCEEDINGS OF THE VLDB ENDOWMENT,13(7),1078-1090.
MLA Liu, Jihang,et al."LB+-Trees: Optimizing Persistent Index Performance on 3DXPoint Memory".PROCEEDINGS OF THE VLDB ENDOWMENT 13.7(2020):1078-1090.

入库方式： OAI收割

来源：计算技术研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。