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Fast response, storage efficiency, fault tolerance and graceful degradation in face of scarce or spurious inputs make neural networks appropiate tools for Intelligent Computer Systems. But on the other hand, learning alg...

El objetivo de esta tesina es analizar, investigar y desarrollar algoritmos de scheduling para ejecutar eficientemente aplicaciones de procesamiento paralelo sobre arquitecturas multicore y clusters de multicore. Esto im...

Como objetivo inicial de esta tesina se encuentra la investigación de modelos de sincronización para aplicaciones paralelas de alta complejidad computacional sobre cluster de multicores, teniendo en cuenta el auge de e...

The parallel computing model used in this paper, the Collective Computing Model (CCM), is a variant of the well-known Bulk Synchronous Parallel (BSP) model. The synchronicity imposed by the BSP model restricts the set of...

Current performance prediction analytical models try to characterize the performance behavior of actual machines through a small set of parameters. Due to different factors, the predicted times suffer substantial deviati...

Parallel computing on networks of workstations are intensively used in some application areas such as linear algebra operations. Topics such as processing as well as communication hardware heterogeneity are considered so...

Processor and network management have a great impact on the performance of Distributed Memory Parallel Computers. Dynamic Process Migration allows load balancing and communication balancing at execution time. Managing th...

InfiniBand (IBA) technology was developed to address the performance issues associated with messages movement among Endnodes and computer I/O devices. However, InfiniBand is also widely deployed within high performance c...

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