Synthesis of 2-level combinatorial circuits with PKmin

In this paper a new design tool is presented that is useful in automated synthesis of combinatorial logic. PKmin program is devoted for synthesis of 2-level circuits composed of gates and PLAs, multi-level circuits and a functional decomposition of logical functions for LUT-based logic implementations in FPGA. It has been built on the basis of the research conducted at Cracow University of Technology. In the paper design algorithms implemented in PKmin are mutually compared. Then, an experimental efficiency comparison of gate and PLA-based 2-level synthesis with PKmin and Espresso design tools is reported

Minimize Logic Synthesis FPGA – Extraction And Substitution Problems

The objective of multi-level logic synthesis of FPGA is to find the “best” multi-level structure, where “best” in this case means an equivalent presentation that is optimal with respect to various parameters such as size, speed or power consumption... Five basic operations are used in order to reach this goal: decomposition, extraction, factoring, substitution and collapsing. In this paper we propose a novel application of Walsh spectral transformation to the evaluation of Boolean function correlation. In particular, we present an algorithm with approach to solve the problems of extraction and substitution based on the use of Walsh spectral presentation. The method, operating in the transform domain, has appeared to be more advantageous than traditional approaches, using operations in the Boolean domain, concerning both memory occupation and execution time on some classes of functions

Advances in Functional Decomposition: Theory and Applications

Functional decomposition aims at finding efficient representations for Boolean functions. It is used in many applications, including multi-level logic synthesis, formal verification, and testing. This dissertation presents novel heuristic algorithms for functional decomposition. These algorithms take advantage of suitable representations of the Boolean functions in order to be efficient. The first two algorithms compute simple-disjoint and disjoint-support decompositions. They are based on representing the target function by a Reduced Ordered Binary Decision Diagram (BDD). Unlike other BDD-based algorithms, the presented ones can deal with larger target functions and produce more decompositions without requiring expensive manipulations of the representation, particularly BDD reordering. The third algorithm also finds disjoint-support decompositions, but it is based on a technique which integrates circuit graph analysis and BDD-based decomposition. The combination of the two approaches results in an algorithm which is more robust than a purely BDD-based one, and that improves both the quality of the results and the running time. The fourth algorithm uses circuit graph analysis to obtain non-disjoint decompositions. We show that the problem of computing non-disjoint decompositions can be reduced to the problem of computing multiple-vertex dominators. We also prove that multiple-vertex dominators can be found in polynomial time. This result is important because there is no known polynomial time algorithm for computing all non-disjoint decompositions of a Boolean function. The fifth algorithm provides an efficient means to decompose a function at the circuit graph level, by using information derived from a BDD representation. This is done without the expensive circuit re-synthesis normally associated with BDD-based decomposition approaches. Finally we present two publications that resulted from the many detours we have taken along the winding path of our research