Mostrar el registro sencillo del ítem

dc.contributor.authorQuislant-del-Barrio, Ricardo 
dc.contributor.authorFernández-Vega, Iván
dc.contributor.authorSerralvo, Eduardo
dc.contributor.authorGutiérrez-Carrasco, Eladio Damián 
dc.contributor.authorPlata-González, Óscar Guillermo 
dc.date.accessioned2022-09-27T08:39:28Z
dc.date.available2022-09-27T08:39:28Z
dc.date.created2022-09-27
dc.date.issued2022-09-21
dc.identifier.urihttps://hdl.handle.net/10630/25089
dc.description.abstractTime series analysis is an important research topic and a key step in monitoring and predicting events in many fields. Recently, the Matrix Profile method, and particularly two of its Euclidean-distance-based implementations – SCRIMP and SCAMP – have become the state-of-the-art approaches in this field. Those algorithms bring the possibility of obtaining exact motifs and discords from a time series, which can be used to infer events, predict outcomes, detect anomalies and more. While matrix profile is embarrassingly parallelizable, we find that autovectorization techniques fail to fully exploit the SIMD capabilities of modern CPU architectures. In this paper, we develop custom-vectorized SCRIMP and SCAMP implementations based on AVX2 and AVX-512 extensions, which we combine with multi-threading techniques aimed at exploiting the potential of the underneath architectures. Our experimental evaluation, conducted using real data, shows a performance improvement of more than 4× with respect to the autovectorization.es_ES
dc.description.sponsorshipUniversidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.es_ES
dc.language.isoenges_ES
dc.publisherSARTECOes_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.subjectAnálisis de series temporales - Congresoses_ES
dc.subjectAlgoritmos - Congresoses_ES
dc.subjectArquitectura de ordenadores - Congresoses_ES
dc.subject.otherTime series analysises_ES
dc.subject.otherMatrix profilees_ES
dc.subject.otherParallelismes_ES
dc.subject.otherVectorizationes_ES
dc.titleExploiting Vector Extensions to Accelerate Time Series Analysis.es_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.centroE.T.S.I. Informáticaes_ES
dc.relation.eventtitleJornadas SARTECOes_ES
dc.relation.eventplaceAlicantees_ES
dc.relation.eventdateSeptiembre 2022es_ES


Ficheros en el ítem

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem