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dc.date.accessioned 2012-10-10T15:46:01Z
dc.date.available 2012-10-10T15:46:01Z
dc.date.issued 1999
dc.identifier.uri http://hdl.handle.net/10915/22225
dc.description.abstract A parallel program, when running, can be conceived a set of parallel components (tasks) which can be executed according to sorne precedence relationship. In this case efficient scheduling of tasks permits to take full.advantage of the computational power provided by a multiprocessor or a multicomputer system. This involves the assignment of partially ordered tasks onto the system architecture processing components. Ihis work shows the problem of allocating a number of nonidentical tasks in a multiprocessor or multicomputer system. Ihe model assumes that the system consists of a number of identical processors and only one task may execute on a processor at a time. All schedules and tasks are nonpreeptive. Ihe well-known Grabam's [8] list scheduling algorithm (LSA) is contrasted with an evolutionary approach using the indirect-decode representation. en
dc.format.extent 6 p. es
dc.language en es
dc.title An evolutionary approach to the parallel task scheduling problem en
dc.type Objeto de conferencia es
sedici.creator.person Esquivel, Susana Cecilia es
sedici.creator.person Gatica, Claudia Ruth es
sedici.creator.person Gallard, Raúl Hector es
sedici.description.note Eje: Redes y sistemas inteligentes es
sedici.subject.materias Ciencias Informáticas es
sedici.subject.keyword evolutionary approach en
sedici.subject.keyword scheduling problem en
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 1999-05 es
sedici.relation.event I Workshop de Investigadores en Ciencias de la Computación es
sedici.description.peerReview peer-review es
sedici.subject.acmcss98 ARTIFICIAL INTELLIGENCE es
sedici.subject.acmcss98 Scheduling es
sedici.subject.acmcss98 Parallel 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)