Finite state automata (FSA) are ubiquitous in computer science. Two of the most important algorithms for FSA processing are the conversion of a non-deterministic finite automaton (NFA) to a deterministic finite automaton (DFA), and then the production of the unique minimal DFA for the original NFA. We exhibit a parallel disk-based algorithm that uses a cluster of 29 commodity computers to produce an intermediate DFA with almost two billion states and then continues by producing the corresponding unique minimal DFA with less than 800,000 states. The largest previous such computation in the literature was carried out on a 512-processor CM-5 supercomputer in 1996. That computation produced an intermediate DFA with 525,000 states and an unreported number of states for the corresponding minimal DFA. The work is used to provide strong experimental evidence satisfying a conjecture on a series of token passing networks. The conjecture concerns stack sortable permutations for a finite stack and a 3-buffer. The origins of this problem lie in the work on restricted permutations begun by Knuth and Tarjan in the late 1960s. The parallel disk-based computation is also compared with both a single-threaded and multi-threaded RAM-based implementation using a 16-core 128 GB large shared memory computer.
We present a parallel algorithm for the minimization of deterministic finite state automata (DFAs) and discuss its implementation on a connection machine CM-5 using data parallel and message passing models. We show that its time complexity on a p processor EREW PRAM (p spl les n) for inputs of size n is O([n log sup 2 n p]+log n log p) uniformly on almost all instances. The work done by our algorithm is thus within a factor of O(log n) of the best known sequential algorithm. The space used by our algorithm is linear in the input size. The actual resource requirements of our implementations are consistent with these estimates. Although parallel algorithms have been proposed for this problem in the past, they are not practical. We discuss the implementation details and the experimental results.  In this paper, we have considered the state minimization problem for Deterministic Finite Automata (DFA). An efficient parallel algorithm for solving the problem on an arbitrary CRCW PRAM has been proposed. For n number of states and k number of inputs in ? of the DFA to be minimized, the algorithm runs in O(kn log n) time and uses O(n log n) processors.