Evolving more efficient digital circuits by allowing circuit layout evolution and multi-objective fitness

We use evolutionary search to design combinational logic circuits. The technique is based on evolving the functionality and connectivity of a rectangular array of logic cells whose dimension is defined by the circuit layout. The main idea of this approach is to improve quality of the circuits evolved by the GA by reducing the number of active gates used. We accomplish this by combining two ideas: 1) using multi-objective fitness function; 2) evolving circuit layout. It will be shown that using these two approaches allows us to increase the quality of evolved circuits. The circuits are evolved in two phases. Initially the genome fitness in given by the percentage of output bits that are correct. Once 100% functional circuits have been evolved, the number of gates actually used in the circuit is taken into account in the fitness function. This allows us to evolve circuits with 100% functionality and minimise the number of active gates in circuit structure. The population is initialised with heterogeneous circuit layouts and the circuit layout is allowed to vary during the evolutionary process. Evolving the circuit layout together with the function is one of the distinctive features of proposed approach. The experimental results show that allowing the circuit layout to be flexible is useful when we want to evolve circuits with the smallest number of gates used. We find that it is better to use a fixed circuit layout when the objective is to achieve the highest number of 100% functional circuits. The two-fitness strategy is most effective when we allow a large number of generations

Genetic algorithm approach to find the best input variable partitioning

Conference PaperThis paper presents a variable partition algorithm which combines the quasi-reduced ordered multiple-terminal multiple-valued decision diagrams and genetic algorithms (GAs). The algorithm is better than the previous techniques which find a good functional decomposition by non-exhaustive search and expands the range of searching for the best decomposition providing the optimal subtable multiplicity. The possible solutions are evaluated using the gain of decomposition for a multiple-output multiple-valued logic function. The distinct feature of GA is the possible solutions being coded by real numbers. Here the simplex-based crossover is proposed to use for the recombination stage of GA. It permits to increase the GA coverag

Regularity and Symmetry as a Base for Efficient Realization of Reversible Logic Circuits

We introduce a Reversible Programmable Gate Array (RPGA) based on regular structure to realize binary functions in reversible logic. This structure, called a 2 * 2 Net Structure, allows for more efficient realization of symmetric functions than the methods shown by previous authors. In addition, it realizes many non-symmetric functions even without variable repetition. Our synthesis method to RPGAs allows to realize arbitrary symmetric function in a completely regular structure of reversible gates with smaller “garbage” than the previously presented papers. Because every Boolean function is symmetrizable by repeating input variables, our method is applicable to arbitrary multi-input, multi-output Boolean functions and realizes such arbitrary function in a circuit with a relatively small number of garbage gate outputs. The method can be also used in classical logic. Its advantages in terms of numbers of gates and inputs/outputs are especially seen for symmetric or incompletely specified functions with many outputs

Minimizing AND-EXOR Expressions for Multiple-Valued Two-Input Logic Functions (Extended Abstract)

A minimum ESOP (Exclusive-OR Sum-of-Products) form of a logic function f is an AND-EXOR 2-level expression of f having the minimum number of product terms. In the paper we deal with multiple-valued 2-input logic functions f , and give an algorithm to find a minimum ESOP form of a given function f in polynomial time

LOT: Logic Optimization with Testability - new transformations for logic synthesis

A new approach to optimize multilevel logic circuits is introduced. Given a multilevel circuit, the synthesis method optimizes its area while simultaneously enhancing its random pattern testability. The method is based on structural transformations at the gate level. New transformations involving EX-OR gates as well as Reed–Muller expansions have been introduced in the synthesis of multilevel circuits. This method is augmented with transformations that specifically enhance random-pattern testability while reducing the area. Testability enhancement is an integral part of our synthesis methodology. Experimental results show that the proposed methodology not only can achieve lower area than other similar tools, but that it achieves better testability compared to available testability enhancement tools such as tstfx. Specifically for ISCAS-85 benchmark circuits, it was observed that EX-OR gate-based transformations successfully contributed toward generating smaller circuits compared to other state-of-the-art logic optimization tools