Biological cells possess important characteristics, such as energy efficiency, self-reproduction, and miniature scale, that make them attractive for many applications. Examples include embedded intelligence in materials, sensing, smart medicine, and nanoscale fabrication. Vast numbers of programmed cells executing in parallel will enable cheap computation. This abstract argues that individual cells are programmable, and presents a programming paradigm for colonies of cells. In such environments, where individual elements have limited resources, aggregation into groups is useful for specialization, fault-tolerance, and resource allocation.
Time taken is proportional to the local density of processors, even in an asynchronous setting.
The physical embedding of the amorphous comp uter is used to derive an upper bound on the number and density of grou ps formed. Simulation results and example applications are presented. By implementing the Gray-Scott model on an amorph ous computer simulation, we show that the patterns obtained by uniform discretisation can also be realised qualitatively on irregul ar, amorphous discretisations if diffusion is modelled correctly . Recent developments in microfabrication and nanotechnology will enable the inexpensive manufacturing of massive numbers of tiny computing elements with sensors and actuators. New programming paradigms are required for obtaining organized and coherent behavior from the cooperation of large numbers of unreliable processing elements that are interconnected in unknown, irregular, and possibly time-varying ways.