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dc.date.accessioned 2012-10-31T18:14:17Z
dc.date.available 2012-10-31T18:14:17Z
dc.date.issued 2000-10
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/23361
dc.description.abstract Many parallel applications do not completely fit into the data parallel model. Although these applications contain data parallelism, task parallelism is needed to represent the natural computation structure or enhance performance. To combine the easiness of programming of the data parallel model with the efficiency of the task parallel model allows to parallel forms to be nested, giving Nested parallelism. In this work, we examine the solutions provided to N ested parallelism in two standard parallel programming platforms, HPF and MPI. Both their expression capacity and their efficiency are compared on a Cray- 3TE, which is distributed memory machine. Finally, an additional speech about the use of the methodology proposed for MPI is done on two different architectures es
dc.language en es
dc.subject nested parallel model en
dc.subject Parallel programming es
dc.subject divide and conquer technique en
dc.title Supporting nested parallelism en
dc.type Objeto de conferencia es
sedici.creator.person Gonzalez, Jesús A. es
sedici.creator.person León, Coromoto es
sedici.creator.person Piccoli, María Fabiana es
sedici.creator.person Printista, Alicia Marcela es
sedici.creator.person Roda García, José Luis es
sedici.creator.person Rodríguez, Casiano es
sedici.creator.person Sande Gonzalez, Francisco de es
sedici.description.note I Workshop de Procesamiento Distribuido y Paralelo (WPDP) 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 2000-10
sedici.relation.event VI 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)