Mostra el registre d'ítem simple

dc.contributor.authorTouma, Rizkallah
dc.contributor.authorQueralt Calafat, Anna
dc.contributor.authorCortés, Toni
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors
dc.contributor.otherBarcelona Supercomputing Center
dc.date.accessioned2020-05-07T12:22:19Z
dc.date.available2021-11-12T01:32:50Z
dc.date.issued2019-11-12
dc.identifier.citationTouma, 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.
dc.identifier.issn0167-739X
dc.identifier.otherhttps://arxiv.org/abs/2005.11259
dc.identifier.urihttp://hdl.handle.net/2117/186696
dc.description.abstractData 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 memory and/or computation overhead. In this paper, we present CAPre, a novel prefetching system for Persistent Object Stores based on static code analysis of object-oriented applications. CAPre generates the predictions at compile-time and does not introduce any overhead to the application execution. Moreover, CAPre is able to predict large amounts of objects that will be accessed in the near future, thus enabling the object store to perform parallel prefetching if the objects are distributed, in a much more aggressive way than in schema-based prediction algorithms. We integrate CAPre into a distributed Persistent Object Store and run a series of experiments that show that it can reduce the execution time of applications from 9% to over 50%, depending on the nature of the application and its persistent data model.
dc.description.sponsorshipThis work has been supported by the European Union’s Horizon 2020 research and innovation program under the BigStorage European Training Network (ETN) (grant H2020-MSCA-ITN-2014- 642963), the Spanish Ministry of Science and Innovation (contract TIN2015-65316) and the Generalitat de Catalunya, Spain (contract 2014-SGR-1051).
dc.format.extent16 p.
dc.language.isoeng
dc.publisherElsevier
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights©2019 Elsevier
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectÀrees temàtiques de la UPC::Informàtica::Arquitectura de computadors
dc.subject.lcshObject-oriented programming (Computer science)
dc.subject.lcshCache memory
dc.subject.otherPersistent object stores
dc.subject.otherStatic code analysis
dc.subject.otherData prefetching
dc.subject.otherParallel prefetching
dc.subject.otherObject-oriented programming languages
dc.titleCAPre: Code-Analysis based Prefetching for Persistent object stores
dc.typeArticle
dc.subject.lemacProgramació orientada a l'objecte (Informàtica)
dc.subject.lemacMemòria cau
dc.contributor.groupUniversitat Politècnica de Catalunya. CAP - Grup de Computació d'Altes Prestacions
dc.identifier.doi10.1016/j.future.2019.10.023
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S0167739X19314293
dc.rights.accessOpen Access
local.identifier.drac28099836
dc.description.versionPostprint (author's final draft)
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO//TIN2015-65316-P/ES/COMPUTACION DE ALTAS PRESTACIONES VII/
dc.relation.projectidinfo:eu-repo/grantAgreement/AGAUR/V PRI/2014 SGR 1051
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/642963/EU/BigStorage: Storage-based Convergence between HPC and Cloud to handle Big Data/BigStorage
local.citation.authorTouma, R.; Queralt, A.; Cortés, T.
local.citation.publicationNameFuture generation computer systems
local.citation.volume111
local.citation.startingPage491
local.citation.endingPage506


Fitxers d'aquest items

Thumbnail

Aquest ítem apareix a les col·leccions següents

Mostra el registre d'ítem simple