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dc.date.accessioned 2012-10-29T12:26:28Z
dc.date.available 2012-10-29T12:26:28Z
dc.date.issued 2002-10
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/23103
dc.description.abstract The N-body problem is often characterized by the necessity to interact each of the N bodies with every other one. Its principal problem is the time spent in force computation. Computing the force among a set of N bodies can be done in a straightforward way by computing all N2 pair wise interactions. However, a number of more efficient algorithms have been proposed, these can approximate the forces among N bodies in close to linear time. The Barnes-Hut algorithm is one these. Barnes-Hut algorithm is suitable to be resolve in parallel. Several parallel challenges have been don, most of them for shared memory machine. In this paper, we describe the design of portable and efficient parallel implementation of adaptive N-body method: Barnes-Hut algorithm. Our propose is based on a regular communication pattern and work partitioning scheme that allows to apply nested data parallelism and to obtain portable solution. Finally, our aim is not simply to develop an efficient implementation of one algorithm, but show how a programming model can be applied in problems not suitable to it, in first instance. es
dc.format.extent 478-489 es
dc.language en es
dc.subject comunicación es
dc.subject N-body problems en
dc.subject Parallel es
dc.subject Parallel programming models en
dc.subject Languages es
dc.subject Communication pattern en
dc.subject Algorithms es
dc.subject Data partition en
dc.subject Balanced workload en
dc.title Introducing nested data parallel in barnes hut algorithm en
dc.type Objeto de conferencia es
sedici.creator.person Fuentes, M. es
sedici.creator.person Piccoli, María Fabiana es
sedici.creator.person Printista, Alicia Marcela es
sedici.description.note Eje: Lenguajes es
sedici.subject.materias Ciencias Informáticas es
sedici.description.fulltext true es
mods.originInfo.place Red de Universidades con Carreras en Informática (RedUNCI) es
sedici.subtype Objeto de conferencia es
sedici.rights.license Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
sedici.rights.uri http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
sedici.date.exposure 2002-10
sedici.relation.event VIII Congreso Argentino de Ciencias de la Computación es
sedici.description.peerReview peer-review es


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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)