Soliton-like behavior in automata
Physica D
Cellular automata machines: a new environment for modeling
Cellular automata machines: a new environment for modeling
A new kind of science
Evolution of Parallel Cellular Machines: The Cellular Programming Approach
Evolution of Parallel Cellular Machines: The Cellular Programming Approach
Parallel Substitution Algorithm: Theory and Application
Parallel Substitution Algorithm: Theory and Application
Implementing Cellular Automata Based Models on Parallel Architectures: The CAPP Project
PaCT '999 Proceedings of the 5th International Conference on Parallel Computing Technologies
Simulating Spatial Dynamics by Probabilistic Cellular Automata
ACRI '01 Proceedings of the 5th International Conference on Cellular Automata for Research and Industry
Methods for Parallel Simulations of Surface Reactions
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
Parallel simulation of asynchronous cellular automata evolution
ACRI'06 Proceedings of the 7th international conference on Cellular Automata for Research and Industry
A parallel implementation of the cellular potts model for simulation of cell-based morphogenesis
ACRI'06 Proceedings of the 7th international conference on Cellular Automata for Research and Industry
Composing fine-grained parallel algorithms for spatial dynamics simulation
PaCT'05 Proceedings of the 8th international conference on Parallel Computing Technologies
Using multi core computers for implementing cellular automata systems
PaCT'11 Proceedings of the 11th international conference on Parallel computing technologies
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Simulating spatial dynamics in physics by Cellular Automata (CA) requires very large computation power, and, hence, CA simulation algorithms are to be implemented on multiprocessors. The preconceived opinion, that no much effort is required to obtain highly efficient coarse grained parallel CA algorithm, is not always true. In fact, a great variety of CA modifications coming into practical use need appropriate, sometimes sophisticated, methods of CA algorithms parallel implementation. Proceeding from the above a general approach to CA parallelization, based on domain decomposition correctness conditions, is formulated. Starting from the correctness conditions particular parallelization methods are developed for the main classes of CA simulation models: synchronous CA with multi-cell updating rules, asynchronous probabilistic CA, and CA compositions. Examples and experimental results are given for each case.