Scheduling parallel jobs for multiphysics simulators

Real problem simulations involving physic phenomena can demand too much execution time. To improve the performance of these simulations it is necessary to have an approach to parallelize the processes that compose the simulation. MPhyScaS (Multi-Physics and Multi-Scale Solver Environment) is an environment dedicated to the automatic development of simulators. Each MPhyScaS simulation demands a great amount of time. To parallelize MPhyScaS simulations, the approach used should define a hierarchical parallel structure. The aim of the work herein presented is to improve the performance of clusters in the processing of MPhyScaS simulations which are composed by a set of dependent tasks by scheduling them. The presented model is based on Genetic Algorithms (GA) to schedule the parallel tasks following MPhyScaS architecture dependence restrictions. The communication between processors must also be considered in this scheduling. Therefore, a trade off must be found between the execution of processes and the time necessary for these processes to communicate with each other.