What is it about?
Data centers are embracing the disaggregated memory (DM) architecture to improve resource efficiency and save costs. B+ trees are usually chosen to store and retrieve data on DM, but are they suitable for DM? This paper proposes the radix tree as a better choice and optimizes it to fit DM.
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Why is it important?
Today's cloud data centers have long suffered from low memory utilization (< 60%). Disaggregated memory (DM) is an increasingly prevalent architecture proposed to address such an issue. However, as DM decouples the computing and memory resources, traditional indexing solutions do not work well. Our findings show that the performance of existing B+ trees on DM is up to 10.8 times lower than the theoretical upper bound.
Perspectives
This data structure is specifically designed for disaggregated memory. It also contains some useful and general designs, such as a read delegation and write combining design, a pure lock-free ART design. I hope you find this paper interesting.
Xuchuan Luo
Fudan University
This paper innovatively proposes to use radix trees as range index data structures on disaggregated memory (DM). This work can be viewed as a guideline on how to design efficient range indexes on DM.
Jiacheng Shen
The Chinese University of Hong Kong
Read the Original
This page is a summary of: A Memory-Disaggregated Radix Tree, ACM Transactions on Storage, May 2024, ACM (Association for Computing Machinery),
DOI: 10.1145/3664289.
You can read the full text:
Resources
The Original Paper in OSDI 2023
The preliminary version of this paper appears in Proceedings of the 17th USENIX Symposium on Operating Systems Design and Implementation (OSDI ’23), pages 553-571.
The Open-Source Repository at GitHub
The artifact provides the source codes and automated scripts to reproduce all the experiment results in the paper.
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