Dynamic data type optimization and memory assignment methodologies

Bartzas, A; Baloukas, C; Soudris, D; Potamianos, K; Ieromnimon, F; Voros, NS

dc.contributor.author	Bartzas, A	en
dc.contributor.author	Baloukas, C	en
dc.contributor.author	Soudris, D	en
dc.contributor.author	Potamianos, K	en
dc.contributor.author	Ieromnimon, F	en
dc.contributor.author	Voros, NS	en
dc.date.accessioned	2014-03-01T02:52:39Z
dc.date.available	2014-03-01T02:52:39Z
dc.date.issued	2010	en
dc.identifier.issn	03029743	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/35973
dc.subject.other	Broadband wireless	en
dc.subject.other	Computing platform	en
dc.subject.other	Dynamic data	en
dc.subject.other	Dynamic data types	en
dc.subject.other	Dynamic events	en
dc.subject.other	Energy consumption	en
dc.subject.other	Execution time	en
dc.subject.other	IEEE802.16	en
dc.subject.other	Memory resources	en
dc.subject.other	Re-configurable	en
dc.subject.other	Resource requirements	en
dc.subject.other	Telecom systems	en
dc.subject.other	Technical presentations	en
dc.subject.other	Telecommunication systems	en
dc.subject.other	Time measurement	en
dc.subject.other	Timing circuits	en
dc.subject.other	Optimization	en
dc.title	Dynamic data type optimization and memory assignment methodologies	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1007/978-3-642-11802-9_22	en
heal.identifier.secondary	http://dx.doi.org/10.1007/978-3-642-11802-9_22	en
heal.publicationDate	2010	en
heal.abstract	It is evident that most new computing platforms are becoming more and more complex encapsulating multiple cores and reconfigurable elements. This offers the designers a multitude of resources. It is their responsibility to exploit the available resources in such a way to efficiently implement their applications. Furthermore, the complexity of the applications that run on such platforms is increasing as well. Applications running on such platforms need to cope with dynamic events and have their resource requirements vary during the execution time. In order to cope with this dynamism applications rely in the usage of dynamic data. Applications use containers such as dynamic data types in order to store and retrieve these dynamic data. In this work a set of methodologies that is able to optimize the containers holding the dynamic data and efficiently assign them on the available memory resources is presented. The proposed approach is evaluated in a scheduler for an IEEE802.16-based broadband wireless telecom system and a 3D game application, achieving reductions in the memory energy consumption of 32% and 51% respectively. © 2010 Springer Berlin Heidelberg.	en
heal.journalName	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en
dc.identifier.doi	10.1007/978-3-642-11802-9_22	en
dc.identifier.volume	5953 LNCS	en
dc.identifier.spage	175	en
dc.identifier.epage	185	en