Memory BIST area estimator using Artificial Neural Networks

摘要

Time to market constraints pushes more and more designers to make area estimations early during the design process. Estimating the Built-In Self Test (BIST) area is only possible once the different design memories BIST are synthesized. This is time consuming and not realistic for a large circuit such as a SOC which can include hundreds of memories. In this paper we propose a push button solution for BIST area estimation called BARES based on Artificial Neuronal Networks handling. Experiments have been performed on different STMICROELECTRONICS BIST memories and results prove the efficiency of the proposed method.