A Survey of Relevant Literature
Sequential synthesis offers a collection of problems that can be modeled by FSM equations under synchronous composition. Some have been addressed in the past with various techniques in different logic synthesis applications. In place of designing a huge monolithic FSM and then optimizing it by state reduction and encoding, it is convenient to work with a network of smaller FSMs. However, if each of them is optimized in isolation, part of the implementation flexibility is lost, because no use is made of the global network information. Hierarchical optimization calls for optimizing the FSMs of a network capturing the global network information by means of don’t care conditions. The goal of hierarchical optimization is to optimize the FSMs of a network capturing the global network information by means of don’t care conditions. This paradigm follows the approach taken in multi-level combinational synthesis since the beginning[29,27], where a lot of effort has been invested in capturing the don’t cares conditions and devising efficient algorithms to compute them or their subsets [95, 54, 44, 57].