Examinando por Materia "equations"

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    Handling heterogeneity in networked virtual environments
    (MIT PRESS, 2003-02-01) Trefftz, H; Marsic, I; Zyda, M; Universidad EAFIT. Departamento de Ingeniería de Sistemas; I+D+I en Tecnologías de la Información y las Comunicaciones
    The availability of inexpensive and powerful graphics cards as well as fast Internet connections make networked virtual environments viable for millions of users and many new applications. It is therefore necessary to cope with the growing heterogeneity that arises from differences in computing power, network speed, and users' preferences. This paper describes an architecture that accommodates the heterogeneity while allowing a manager to define systemwide policies. One of the main objectives of our scheme is to allow slower nodes to participate in the session by preventing fast nodes from flooding slow nodes with too many messages. Policies and users' preferences can be expressed as simple linear equations forming a model that describes the system as a whole as well as its individual components. When solutions to this model are mapped back to the problem domain, viable solutions that accommodate heterogeneity and system policies are obtained. For example, slower nodes may receive less frequent updates than faster ones for one or several information streams. The results of our experiments with a proof-of-concept system are described.
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    On The Mathematics of Musical Measures and Their Relation to Geometry
    (Universidad EAFIT, 2023) Lugos Abarca, Josué Alexis
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    Ítem
    Solving large systems of linear equations on GPUs
    (Springer Verlag, 2018-01-01) Llano-Ríos T.F.; Ocampo-García J.D.; Yepes-Ríos J.S.; Correa-Zabala F.J.; Trefftz C.; Universidad EAFIT. Departamento de Ingeniería de Sistemas; I+D+I en Tecnologías de la Información y las Comunicaciones
    Graphical Processing Units (GPUs) have become more accessible peripheral devices with great computing capacity. Moreover, GPUs can be used not only to accelerate the graphics produced by a computer but also for general purpose computing. Many researchers use this technique on their personal workstations to accelerate the execution of their programs and have often encountered that the amount of memory available on GPU cards is typically smaller than the amount of memory available on the host computer. We are interested in exploring approaches to solve problems with this restriction. Our main contribution is to devise ways in which portions of the problem can be moved to the memory of the GPU to be solved using its multiprocessing capabilities. We implemented on a GPU the Jacobi iterative method to solve systems of linear equations and report the details from the results obtained, analyzing its performance and accuracy. Our code solves a system of linear equations large enough to exceed the card’s memory, but not the host memory. Significant speedups were observed, as the execution time taken to solve each system is faster than those obtained with Intel® MKL and Eigen, libraries designed to work on CPUs. © Springer Nature Switzerland AG 2018.