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The models I wish to parallelise are implemented on a lattice (usually a hexagonal one) consisting of ~100000 cells (though I'd like to use more), and the non-parallelised algorithm for running them looks like this: There are also some complications to do with the boundary conditions, but I imagine these won't pose much difficulty for parallelisation. (2002) Artificially Evolved Asynchronous Cellular Automata for the Density Task. Moreover, the general construction and the proof also applies to the more general class of synchronous automata networks (inhomogeneous networks of automata over directed graphs, allowing external inputs – which includes cellular automata as a special case), showing constructively how their behaviour may be asynchronously realized by a corresponding asynchronous automata network.We analyze the properties of a synchronous and of various asynchronous methods to iterate cellular automata.Product datasheet Upgrade Price Guarantee Compatible with Windows 10, 8.1, 8, 7, Vista and XP, 32 Bit / 64 Bit Editions New language versions: Chinese - Lithuanian - Japanese - Polski - Romanian - Spanish - Czech Update Star is compatible with Windows platforms.

The synchronous approach assumes the presence of a global clock to ensure all cells are updated together. Nehaniv in 1998) allows one to emulate exactly the behaviour of a synchronous cellular automaton via an asynchronous one constructed as a simple modification of the synchronous cellular automaton (Nehaniv 2002).

Unfortunately it isn't quite straightforward to parallelise such a model, and it isn't at all clear to me how to go about it.

I'm aware that there is literature on the subject, but it all seems to be aimed at hardcore computer scientists who are interested in the details of algorithmic complexity, rather than someone like me who just wants a description of something I can implement, and consequently I find it rather inpenetrable.

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