Simulation has become an indispensable tool for researchers to explore systems without having recourse to real experiments. In this context multi-agent systems are often used to model and simulate complex systems. Depending on the characteristics of the modelled system, methods used to represent the system may vary. Whatever the modelling techniques used, increasing the size and the precision of a model increases the amount of computation needed, requiring the use of parallel systems when it becomes too large. Usually, to efficiently run on parallel resources, the model must be adapted to be distributed. In this paper, we propose a new modelling approach, based on nested graphs, that allows the design of large, complex and multi-scale multi-agent models which can be efficiently distributed on parallel resources. A PDMAS (Parallel and Distributed Multi-Agent Platform) that supports this approach and efficiently run parallel multi-agent models is introduced.