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The approach consists of an analytical model for the energy consumption of a parallel computation in fork\u2010join form on dynamic voltage frequency scaling processors, a theoretical specification of an energy\u2010optimal frequency\u2010scaled state, and the energy minimization by computing optimal scaling factors. For larger numbers of tasks, the approach is extended by scheduling algorithms, which exploit the analytical result and aim at a reduction of the energy. Energy measurements of a complex numerical method and the SPEC CPU2006 benchmarks as well as simulations for a large number of randomly generated tasks illustrate and validate the energy modeling, the minimization, and the scheduling results. 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