Cellular processing tools for high-performance simulation

Cellular automata offer a powerful modeling approach for complex systems in which global behavior arises from the collective effect of many locally interacting, simple components. Several tools based on CA are providing meaningful results for real-world applications. Cellular automata represent an efficient paradigm for the computer solution of important problems in science and engineering. Moreover, the CA model lets researchers effectively use parallel computers to achieve scalable performance. As researchers use parallel computers to solve scientific problems, they will need problem representations (paradigms) for this class of computers. Abstract mathematical models that offer an implicitly parallel representation of problems better match those architectures, but could benefit from new high-level languages, environments, and techniques. The three should support all the development steps of computational science applications while hiding architectural details from users. Computational science is also an interdisciplinary field in which many areas converge, and developing applications in this field requires the cooperation of people from different domains. Modeling and simulation using parallel cellular methods helps researchers cooperate by offering both a way to code an algorithm and an integrated environment for developing software.