Browsing by Subject "Model driven software development"

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    Architecture framework for mapping parallel algorithms to parallel computing platforms
    (CEUR-WS, 2013) Tekinerdogan, Bedir; Arkin, E.
    Mapping parallel algorithms to parallel computing platforms requires several activities such as the analysis of the parallel algorithm, the definition of the logical configuration of the platform, and the mapping of the algorithm to the logical configuration platform. Unfortunately, in current parallel computing approaches there does not seem to be precise modeling approaches for supporting the mapping process. The lack of a clear and precise modeling approach for parallel computing impedes the communication and analysis of the decisions for supporting the mapping of parallel algorithms to parallel computing platforms. In this paper we present an architecture framework for modeling the various views that are related to the mapping process. An architectural framework organizes and structures the proposed architectural viewpoints. We propose five coherent set of viewpoints for supporting the mapping of parallel algorithms to parallel computing platforms. We illustrate the architecture framework for the mapping of array increment algorithm to the parallel computing platform. Copyright © 2013 for the individual papers by the papers' authors.
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    Model-driven transformations for mapping parallel algorithms on parallel computing platforms
    (MDHPCL, 2013) Arkin, E.; Tekinerdoğan, Bedir
    One of the important problems in parallel computing is the mapping of the parallel algorithm to the parallel computing platform. Hereby, for each parallel node the corresponding code for the parallel nodes must be implemented. For platforms with a limited number of processing nodes this can be done manually. However, in case the parallel computing platform consists of hundreds of thousands of processing nodes then the manual coding of the parallel algorithms becomes intractable and error-prone. Moreover, a change of the parallel computing platform requires considerable effort and time of coding. In this paper we present a model-driven approach for generating the code of selected parallel algorithms to be mapped on parallel computing platforms. We describe the required platform independent metamodel, and the model-to-model and the model-to-text transformation patterns. We illustrate our approach for the parallel matrix multiplication algorithm. Copyright © 2013 for the individual papers by the papers' authors.