Cellular ANTomata as Engines for Highly Parallel Pattern Processing.

One important approach to high-performance computing has a (relatively) simple physical computer architecture emulate virtual algorithmic architectures (VAAs) that are highly optimized for important application domains. We expose the Cellular ANTomaton (CAnt) computing model-cellular automata enhanced with mobile FSMs (Ants)-as a highly efficient VAA for a variety of pattern-processing problems that are inspired by biocomputing applications. We illustrate the CAnt model via a scalable design for an n x n CAnt that solves the following bio-inspired problem in linear time. The Pattern-Assembly Problem. Inputs: a length-n master pattern II and r test patterns pi(0), . . . , pi(r-1), of respective lengths m(0) >= . . . >= m(r-1). The problem: Find every sequence of pi(k)'s, possibly with repetitions, that "assemble" (i.e., concatenate) to produce II; i.e., pi(j0) . . . pi(js-1) = II. Timing: m(1) + . . . + m(r) + O(n) steps, with a quite-small big-O constant.