  Probabilistic cellular automata are prototypes of non equilibrium critical
phenomena. This class of models includes among others the directed percolation
problem (Domany Kinzel model) and the dynamical Ising model. The critical
properties of these models are usually obtained by fine-tuning one or more
control parameters, as for instance the temperature. We present a method for
the parallel evolution of the model for all the values of the control
parameter, although its implementation is in general limited to a fixed number
of values. This algorithm facilitates the sketching of phase diagrams and can
be useful in deriving the critical properties of the model. Since the
criticality here emerges from the asymptotic distribution of some quantities,
without tuning of parameters, our method is a mapping from a probabilistic
cellular automaton with critical behavior to a self organized critical model
with the same critical properties.
