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Dynamically allocating computing nodes to parallel applications is a promising technique for improving the utilization of cluster resources. We introduce the concept of dynamic efficiency which expresses the resource utilization efficiency as a function of time. We propose a simulation framework which enables predicting the dynamic efficiency of a parallel application. It relies on the DPS parallelization framework to which we add direct execution simulation capabilities. The high level flow graph description of DPS applications enables the accurate simulation of parallel applications without needing to modify the application code. Thanks to partial direct execution, simulation times and memory requirements may be reduced. In simulations under partial direct execution, the application's parallel behavior is simulated thanks to direct execution, and the duration of individual operations is obtained from a performance prediction model or from prior measurements. We verify the accuracy of our simulator by comparing the effective running time, respectively the dynamic efficiency, of parallel program executions with the running time, respectively the dynamic efficiency, predicted by the simulator. These comparisons are performed for an LU factorization application under different parallelization and dynamic node allocation strategies