Equivalence checking between SLM and RTL using machine learning techniques

Abstract

The growing complexity of modern digital design makes designers shift toward starting design exploration using high-level languages, and generating register transfer level (RTL) design from system level modeling (SLM) using high-level synthesis or manual transformation. Unfortunately, this translation process is very complex and may introduce bugs into the generated design. In this paper, we propose a novel SLM and RTL sequential equivalence checking method. The proposed method bases on Finite state machines with datapath (FSMD) equivalence checking method. The proposed method recognizes the corresponding path-pairs of FSMDs using machine learning (ML) technique from all the paths. And then it compares the corresponding path-pairs by symbolic simulation. The advantage of our method is that it separates the corresponding path-pairs from all the paths and avoids blind comparisons of path-pairs. Our method can deal with greatly different SLM and RTL designs and dramatically reduce the complexity of the path-based FSMD equivalence checking problem. The promising experimental results show the efficiency and effectiveness of the proposed method.