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Parallel Simulation of Asynchronous Cellular Automata Evolution

机译:异步细胞自动机进化的并行仿真

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For simulating physical and chemical processes on molecular level asynchronous cellular automata with probabilistic transition rules are widely used being sometimes referred to as Monte-Carlo methods. The simulation requires huge cellular space and millions of iterative steps for obtaining the CA evolution representing the real scene of the process. This may be achieved by allocating the CA evolution program onto a multiprocessor system. As distinct from the synchronous Cas which is extremely efficient, the asynchronous case of parallel implementation is stiff. To improve the situation we propose a method for approximating asynchronous CA by a superposition of a number of synchronous ones, each being applied to locally separated blocks forming a partition of the cellular array.
机译:为了在分子水平上模拟物理和化学过程,具有概率转移规则的异步细胞自动机被广泛使用,有时被称为蒙特卡洛方法。该模拟需要巨大的单元空间和数百万个迭代步骤才能获得代表过程真实场景的CA演变。这可以通过将CA演化程序分配到多处理器系统上来实现。与效率极高的同步Cas不同,并行实现的异步情况很严格。为了改善这种情况,我们提出了一种通过多个同步载波的叠加来近似异步CA的方法,每个方法都应用于局部分离的块,这些块形成了蜂窝阵列的一部分。

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