High Level Ageing Vectors Management for Data Intensive Applications

We introduce a new approach to take into account the memory architecture and the memory mapping in behavioral synthesis. We present a new strategy for implementing signals (ageing vectors). We formalize the maturing process and explain how it may generate memory conflicts over several iterations of the algorithm. The final Compatibility Graph indicates the set of valid mappings for every signal. Several experiments are performed with our HLS tool GAUT. Our strategy exhibits a relatively low complexity memory architecture for ageing vectors that permits to tackle complex designs for data intensive applications