The work presented in this paper aims at restricting the input parameter values of the semi-analytical model used in Galics and MoMaF, so as to derive which parameters influence the most the results, e.g., star forma- tion, feedback and halo recycling efficiencies, etc. Our approach is to proceed empirically: we run lots of simulations and derive the correct ranges of values. The computation time needed is so large, that we need to run on a grid of com- puters. Hence, we model Galics and MoMaF execution time and output files size, and run the simulation using a grid middleware: Diet. All the complexity of accessing resources, scheduling simulations and managing data is harnessed by Diet and hidden behind a web portal accessible to the users