Logo des Repositoriums
 

Investigating High Memory Churn via Object Lifetime Analysis to Improve Software Performance

dc.contributor.authorWeninger, Markus
dc.contributor.authorGander, Elias
dc.contributor.authorMössenböck, Hanspeter
dc.contributor.editorKelter, Udo
dc.date.accessioned2022-11-24T10:42:06Z
dc.date.available2022-11-24T10:42:06Z
dc.date.issued2020
dc.description.abstractHigh memory churn occurs when many temporary objects are created and shortly thereafter collected by the garbage collector. Such excessive dynamic allocations negatively impact an application’s performance because (1) a great number of objects has to be allocated on the heap and (2) an increased number of garbage collections is required to collect them. In this paper, we present ongoing research on how to support developers in detecting, understanding and resolving high memory churn in order to improve their application’s performance. Based on a recorded memory trace, an algorithm automatically searches for memory churn hotspots and calculates the age at which objects die within it, since objects that die young are the major contributors to memory churn. Information about these objects, for example their types and allocation sites, can then be inspected in order to locate the problematic code locations. To demonstrate the feasibility and applicability of our approach, we implemented and present a new memory churn analysis feature in AntTracks, our trace-based memory monitoring tool.en
dc.identifier.pissn0720-8928
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/39793
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofSoftwaretechnik-Trends Band 40, Heft 3
dc.relation.ispartofseriesSoftwaretechnik-Trends
dc.subjectperformance
dc.subjectgarbage collection
dc.subjectmemory churn
dc.subjectAntTracks
dc.titleInvestigating High Memory Churn via Object Lifetime Analysis to Improve Software Performanceen
dc.typeText/Conference Paper
gi.citation.endPage63
gi.citation.publisherPlaceBonn
gi.citation.startPage61
gi.conference.date44147
gi.conference.locationLeipzig
gi.conference.sessiontitleSymposium on Software Performance (SSP)

Dateien

Originalbündel
1 - 1 von 1
Lade...
Vorschaubild
Name:
SSP2020_Weninger_Gander.pdf
Größe:
931.96 KB
Format:
Adobe Portable Document Format