@inproceedings{deca248ac27e46a38b29e93eac617611,
title = "CBPGM: A Cache Based Piecewise Geometric Model Index",
abstract = "Recent works on learned indexes have changed the way we look at the decades-old field of Database Management System indexing. However, they are limited to too many hyperparameters, long model construction time, and not taking full advantage of CPU cache and hardware acceleration. In this paper, we propose a Cache Based Piecewise Geometric Model (CBPGM) Index to address these issues with only one hyperparameter and effectively combines a sampling approach to reduce training dataset size that accelerates the construction procedure and aligns models and data to the CPU cache line to improve search performance. Experimental results show that the CBPGM index can improve the construction speed up to 8× and the query speed by 30\% compared with the PGM index.",
keywords = "block sample, cache block, learned index, piecewise linear",
author = "Xiaopei Xu and Guitao Cao and Yan Li",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022 ; Conference date: 09-10-2022 Through 12-10-2022",
year = "2022",
doi = "10.1109/SMC53654.2022.9945100",
language = "英语",
isbn = "9781665452588",
series = "Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2968--2974",
booktitle = "2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022 - Proceedings",
address = "美国",
}