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We present in this paper a framework for performance prediction of parallel programs on hierarchical clusters. This framework is mainly designed for the use by the switching functions in parallel adaptive applications. Indeed, the principal referred objectives by this framework are the accuracy of the prediction and the rapidity of the prediction process.(More)
Performance is one of the key features of parallel and distributed computing systems. For that reason, a significant research effort was invested in the development of approaches in the area of performance modeling and prediction. Since many parallel applications from scientific computing use MPI communication operations to distribute or collect data, we(More)
Recent advances in parallel and distributed computing have made it very challenging for programmers to reach the performance potential of current systems. In addition, recent advances in numerical algorithms and software optimizations have tremendously increased the number of alternatives for solving a problem, which further complicates the software tuning(More)
Recent advances in parallel and distributed computing have made it very challenging for programmers to reach the performance potential of current systems. In addition, recent advances in numerical algorithms and software optimizations have tremendously increased the number of alternatives for solving a problem, which further complicates the software tuning(More)
Due to the increasing diversity and the continuous evolution of existing parallel systems, solving efficiently a target problem by using a single algorithm or writing efficient and portable programs is becoming a challenging task. In this paper, we present a generic framework that integrates performance models with adaptive techniques in order to design(More)
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