Software metadata: Systematic characterization of the memory behaviour of dynamic applications

Bartzas, A; Peon-Quiros, M; Poucet, C; Baloukas, C; Mamagkakis, S; Catthoor, F; Soudris, D; Mendias, JM

dc.contributor.author	Bartzas, A	en
dc.contributor.author	Peon-Quiros, M	en
dc.contributor.author	Poucet, C	en
dc.contributor.author	Baloukas, C	en
dc.contributor.author	Mamagkakis, S	en
dc.contributor.author	Catthoor, F	en
dc.contributor.author	Soudris, D	en
dc.contributor.author	Mendias, JM	en
dc.date.accessioned	2014-03-01T01:34:36Z
dc.date.available	2014-03-01T01:34:36Z
dc.date.issued	2010	en
dc.identifier.issn	0164-1212	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/20772
dc.subject	Analysis	en
dc.subject	Dynamic data types	en
dc.subject	Embedded systems	en
dc.subject	Optimization	en
dc.subject	Profiling	en
dc.subject	Software metadata	en
dc.subject.classification	Computer Science, Software Engineering	en
dc.subject.classification	Computer Science, Theory & Methods	en
dc.subject.other	Analysis	en
dc.subject.other	Appropriate techniques	en
dc.subject.other	Data type	en
dc.subject.other	Dynamic applications	en
dc.subject.other	Dynamic data types	en
dc.subject.other	Engineering process	en
dc.subject.other	Input datas	en
dc.subject.other	Number of cycles	en
dc.subject.other	Representative sample	en
dc.subject.other	Scope of application	en
dc.subject.other	Software applications	en
dc.subject.other	Specific hardware	en
dc.subject.other	Static techniques	en
dc.subject.other	Dynamic analysis	en
dc.subject.other	Embedded software	en
dc.subject.other	Embedded systems	en
dc.subject.other	Input output programs	en
dc.subject.other	Metadata	en
dc.subject.other	Optimization	en
dc.subject.other	Data handling	en
dc.title	Software metadata: Systematic characterization of the memory behaviour of dynamic applications	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.jss.2010.01.001	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.jss.2010.01.001	en
heal.language	English	en
heal.publicationDate	2010	en
heal.abstract	Development of new embedded systems requires tuning of the software applications to specific hardware blocks and platforms as well as to the relevant input data instances. The behaviour of these applications heavily relies on the nature of the input data samples, thus making them strongly data-dependent. For this reason, it is necessary to extensively profile them with representative samples of the actual input data. An important aspect of this profiling is done at the dynamic data type level, which actually steers the designers choice of implementation of these data types. The behaviour of the applications is then characterized, through an analysis phase, as a collection of software metadata that can be used to optimize the system as a whole. In this paper we propose to represent the behaviour of data-dependent applications to enable optimizations, rather than to analyze their structure or to define the engineering process behind them. Moreover, we specifically limit ourselves to the scope of applications dominated by dynamically allocated data types running on embedded systems. We characterize the software metadata that these optimizations require, and we present a methodology, as well as appropriate techniques, to obtain this information from the original application. The optimizations performed on a complete case study, utilizing the extracted software metadata, achieve overall improvements of up to 42% in the number of cycles spent accessing memory when compared to code optimized only with the static techniques applied by GNU G++. (C) 2010 Elsevier Inc. All rights reserved.	en
heal.publisher	ELSEVIER SCIENCE INC	en
heal.journalName	Journal of Systems and Software	en
dc.identifier.doi	10.1016/j.jss.2010.01.001	en
dc.identifier.isi	ISI:000278287700015	en
dc.identifier.volume	83	en
dc.identifier.issue	6	en
dc.identifier.spage	1051	en
dc.identifier.epage	1075	en