APEX: A High-Performance Learned Index on Persistent Memory
Summary: APEX adapts the updatable ALEX learned index for persistent memory, combining distribution-aware models with PM-specific techniques to minimize costly accesses while supporting concurrency and persistence. It delivers up to 15× higher performance than PM indexes and ~42 ms crash recovery. (summarized by gpt-5.6-luna on Jul 24 2026)
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Authors
- 1. Baotong Lu (Chinese University of Hong Kong)
- 2. Jialin Ding (Massachusetts Institute of Technology)
- 3. Eric Lo (Chinese University of Hong Kong)
- 4. Umar Farooq Minhas (Microsoft)
- 5. Tianzheng Wang (Simon Fraser University)
BibTeX Citation
@article{lu_vldb22,
title = {{APEX: A High-Performance Learned Index on Persistent Memory}},
author = {Lu, Baotong and Ding, Jialin and Lo, Eric and Minhas, Umar Farooq and Wang, Tianzheng},
journal = {PVLDB},
series = {{VLDB} '22},
volume = {15},
number = {3},
pages = {597--610},
doi = {10.14778/3494124.3494141},
url = {https://doi.org/10.14778/3494124.3494141},
year = {2022}
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