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CAPre: Code-Analysis based Prefetching for Persistent object stores

Author
Touma, R.; Queralt, A.; Cortes, A.
Type of activity
Journal article
Journal
Future generation computer systems
Date of publication
2020-10
Volume
111
First page
491
Last page
506
DOI
10.1016/j.future.2019.10.023
Project funding
High performance computing VII
Models de Programacio i Entorns d'eXecució PARal.lels
Repository
http://hdl.handle.net/2117/186696 Open in new window
URL
https://www.sciencedirect.com/science/article/pii/S0167739X19314293 Open in new window
Abstract
Data prefetching aims to improve access times to data storage systems by predicting data records that are likely to be accessed by subsequent requests and retrieving them into a memory cache before they are needed. In the case of Persistent Object Stores, previous approaches to prefetching have been based on predictions made through analysis of the store’s schema, which generates rigid predictions, or monitoring access patterns to the store while applications are executed, which introduces mem...
Citation
Touma, R.; Queralt, A.; Cortés, T.. CAPre: Code-Analysis based Prefetching for Persistent object stores. "Future generation computer systems", Octubre 2020, vol. 111, p. 491-506.
Keywords
Data prefetching, Object-oriented programming languages, Parallel prefetching, Persistent object stores, Static code analysis
Group of research
CAP - High Performace Computing Group
IMP - Information Modelling and Processing

Participants