To design parallel numerical algorithms on large scale distributed and heterogeneous platforms, the asynchronous iteration model (AIAC) may be an efficient solution. This class of algorithm is very suitable since it enables communication/computation overlapping and it suppresses all synchronizations between computation nodes. Since target architectures are composed of more than one thousand heterogeneous nodes connected through heterogeneous networks, the need for mapping algorithms is crucial. In this paper, we propose a new mapping algorithm dedicated to the AIAC model. To evaluate our mapping algorithm we implemented it in the JaceP2P programming and executing environment dedicated to AIAC applications and we conducted a set of experiments on the Grid'5000 testbed. Results are very encouraging and show that the use of our algorithm brings an important gain in term of execution time (about 40%).