This report presents the Data-aware Process Networks, a new parallel execution model adapted to the hardware constraints of high-level synthesis, where the data transferts are made explicit. We show that the DPN model is consistant in the meaning where any translation of a sequential program produces an equivalent DPN without deadlocks. Finally, we show how to compile a sequential program to a DPN and how to optimize the input/output and the parallelism.