995 resultados para Vladimir Mayakovsky


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In this article we provide brief descriptions of three classes of schedulers: Operating Systems Process Schedulers, Cluster Systems, Jobs Schedulers and Big Data Schedulers. We describe their evolution from early adoptions to modern implementations, considering both the use and features of algorithms. In summary, we discuss differences between all presented classes of schedulers and discuss their chronological development. In conclusion, we highlight similarities in the focus of scheduling strategies design, applicable to both local and distributed systems.

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Recent developments of high-end processors recognize temperature monitoring and tuning as one of the main challenges towards achieving higher performance given the growing power and temperature constraints. To address this challenge, one needs both suitable thermal energy abstraction and corresponding instrumentation. Our model is based on application-specific parameters such as power consumption, execution time, and asymptotic temperature as well as hardware-specific parameters such as half time for thermal rise or fall. As observed with our out-of-band instrumentation and monitoring infrastructure, the temperature changes follow a relatively slow capacitor-style charge-discharge process. Therefore, we use the lumped thermal model that initiates an exponential process whenever there is a change in processor’s power consumption. Initial experiments with two codes – Firestarter and Nekbone – validate our thermal energy model and demonstrate its use for analyzing and potentially improving the application-specific balance between temperature, power, and performance.

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Key feature of a context-aware application is the ability to adapt based on the change of context. Two approaches that are widely used in this regard are the context-action pair mapping where developers match an action to execute for a particular context change and the adaptive learning where a context-aware application refines its action over time based on the preceding action’s outcome. Both these approaches have limitation which makes them unsuitable in situations where a context-aware application has to deal with unknown context changes. In this paper we propose a framework where adaptation is carried out via concurrent multi-action evaluation of a dynamically created action space. This dynamic creation of the action space eliminates the need for relying on the developers to create context-action pairs and the concurrent multi-action evaluation reduces the adaptation time as opposed to the iterative approach used by adaptive learning techniques. Using our reference implementation of the framework we show how it could be used to dynamically determine the threshold price in an e-commerce system which uses the name-your-own-price (NYOP) strategy.

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This paper introduces a strategy to allocate services on a cloud system without overloading the nodes and maintaining the system stability with minimum cost. We specify an abstract model of cloud resources utilization, including multiple types of resources as well as considerations for the service migration costs. A prototype meta-heuristic load balancer is demonstrated and experimental results are presented and discussed. We also propose a novel genetic algorithm, where population is seeded with the outputs of other meta-heuristic algorithms.

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Trabalho de Projeto apresentado ao Instituto de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Contabilidade e Finanças, sob orientação de Amélia Cristina Ferreira da Silva

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A PhD Dissertation, presented as part of the requirements for the Degree of Doctor of Philosophy from the NOVA - School of Business and Economics

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Référence bibliographique : Rol, 58329

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Tesis (Maestría en Ciencias de la Administración con Especialidad en Producción) U.A.N.L. Fac. de Ingeniería Mecánica y Eléctrica, 1986.

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Tesis (Maestría en Ciencias para la Planificación de Asentamientos Humanos) UANL, 2010.

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Tesis (Doctor en Ciencias Biológicas con Acentuación en Manejo de Vida Silvestre y Desarrollo Sustentable) UANL, 2009.

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Ce mémoire propose une analyse sémio-narrative d’un corpus de dix-neuf contes merveilleux recueillis auprès des conteurs canadiens-français et canadiens-hurons par l’anthropologue Charles-Marius Barbeau, au début du XXe siècle. Après avoir passé en revue les principales théories dans l’approche sémiotique du conte à partir de Vladimir Propp jusqu’à nos jours, nous avons procédé à une étude narrative du corpus selon la méthode du grand folkloriste russe : cela nous a permis d’en montrer la valeur exceptionnelle mais aussi les limites. Nous avons constaté ainsi que le travail sur un corpus inédit peut mener à l’identification de nouveaux éléments dans la structure du conte merveilleux. En poursuivant nos recherches sur les dix-neuf contes recueillis par Barbeau, nous sommes passée du schéma linéaire, syntagmatique de Propp aux modèles logiques de ses continuateurs, particulièrement celui élaboré par Guy Laflèche. Nos analyses ont mis en évidence non seulement le fait que la structure en miroir est un modèle valide auquel une partie des contes merveilleux se plie parfaitement (d’emblée l’exclusivité du schéma de Propp est mise en question, sinon infirmée), mais aussi que tout conte merveilleux est exceptionnellement organisé, structuré (ce qui confirme la théorie de Claude Bremond conformément à laquelle le récit narratif est une alternance de dégradations et d’améliorations). Enfin, la dernière partie du mémoire est une analyse sémio-discursive de notre corpus qui, au lieu d’être une simple accumulation de listes de mots, d’expressions et de figures, tente d’aborder la structure idéologique, grâce à une étude en parallèle d’un conte du corpus et de deux versions littéraires.