The aim of the paper is to present a parallel simulator that allows to use distributed algorithmic to develop artificial neural networks. We have developed an efficient parallel simulator to implement artificial neural networks. This simulator makes use of the parallel properties of connectionist models to make an efficient parallel implementation onto general purpose shared memory MIMD computers. Therefore this simulator naturally leads to build (learning and generalising) neural algorithms that respect the large natural parallel aspects of these models.