This paper presents an optimization method for pseudo-Kronecker expressions of p-valued input two-valued output functions by using multi-place decision diagrams for p2 and p4. A conventional method using extended truth tables requires memory of O (3n) to simplify an n-variable expression, and is only practical for functions of up to n14 variables when p2. The method presented here utilizes multi-place decision diagrams, and can optimize considerably larger problems. Experimental results for up to n39 variables are shown.

The paper describes a parallel algorithm for the manipulation of binary decision diagrams on a shared memory multi-processor system. Binary decision diagrams are very efficient representations of logic functions, and are widely used in computer aided design of logic circuits. Logic operations on logic functions such as AND and OR are reduced to operations on binary decision diagrams representing these functions. Operations on binary decision diagrams are time-consuming in some cases, and a fast manipulation method is needed. As with the manipulation, we focus on the construction of a binary decision diagram from a logic formula, and devised a parallel algorithm for the construction. In the construction, there are many logic operations to be processed, and some of them can be processed in parallel. At first, we introduce an extraction method and a parallel-execution method for such parallelizable operations. This is the parallel execution method for an operation sequence (or a set of operations). To extract more parallelism, we introduce a dynamic expansion method of a logic operation. The dynamic expansion is a method to obtain sub-operations from a logic operation using the modified Shannon's expansion. These sub-operations are executed in parallel and the results of these sub-operations are merged to obtain the result of the original operation. Our parallel algorithm, which is based on the construction of shared binary decision diagrams with the negative edge and the operation cache, is implemented in C on a shared memory multi-processor system Sequent S-81 (CPU 80386 (16 MHz)28, 86.75MB), and applied to multiplier examples and ISCAS benchmarks. The speed-up ratio becomes 14 for multipliers, and becomes 11 for c1908 in ISCAS benchmarks.

Recently, Burch et al. proposed symbolic model checking method to verify sequential machines formally. The method, which is based on logic function manipulation using binary decision diagram, can handle large sequential machines that cannot be handled by the conventional techniques. The expressive power of Computational Tree Logic (CTL), which was used by Burch et al., is not very powerful, for example, CTL cannot describe repetition of events. This papers shows an extension of the symbolic model checking algorithm to Branching time regular temporal logic (BRTL), which has been proposed by the authors as an improvement of CTL in terms of expressive power. The implemented verifier based on the proposed algorithm could verify behaviors of a microprocessor composed of approximately 1,600 gates and 68 flipflops.

Binary Decision Diagrams (BDDs) and Shared Binary Decision Diagrams (SBDDs), which are improved BDDs, are useful for implementing VLSI logic design systems. Recently, these representations, which are graph representations of Boolean functions, have become popular because of their efficiency in terms of time and space. The forms of the BDD vary with the order of the input variables though they represent the same function. The size of the graphs greatly depends on the order. The variable ordering algorithm is one of the most important issues in the application of BDDs. In this paper, we consider methods which reduce the graph size by reordering input variables on a given BDD with a certain variable order. We propose the Minimum-Width Method which gives a considerably good order in a practicable time and space. In the method, the order is determined by width of BDDs as a cost function. In addition, we show the effect of combining our method with the local search method, and also describe the improvement using the threshold. Experimental results show that our method can reduce the size of BDDs remarkably for most examples. The method needs no additional information, such as the topological information of the circuit. The results can be a measure for evaluation of other ordering methods.