CAFCA (Compact Accelerator For Cellular Automata): the metamorphosable machine

Proceedings of IEEE Workshop on FPGA's for Custom Computing Machines Pub Date : 1994-04-10 DOI:10.1109/FPGA.1994.315601

P. Marchal, E. Sanchez

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引用次数: 5

Abstract

Partial differential equations have conventionally formed a basis for mathematical models of continuous systems. Cellular automata provide an alternative approach. The large scope of applications of cellular automata (in biology, physics, operational research, sociology, computer science and so on) will surely increase the need of such a tool. The basic constitutive cells are discrete and ideally suited to simulation by digital computers. Their property of only interacting in a local environment naturally leads to a new idea of processing: cellular processing. In fact, the simulation of cellular automata with mainframe computers, even with parallel multiprocessors, is always slowed down by the input/output bottleneck. This paper describes the architecture of a compact accelerator for cellular automata. This multi-expandable machine is based on a pipeline architecture which concurrently performs computations and displays results. The underlying principle is to spy on the display bus by grabbing the data flow pouring out to the display device and simultaneously to evaluate the state of each automaton in the network. The performance of the machine reaches the video rate: it computes and displays the state of the 1024/spl times/1024 16-bit automata 24 times per second. FPGAs play a key role in the architecture of the system.<>

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CAFCA (Compact Accelerator For Cellular Automata):可变形机器

偏微分方程通常是连续系统数学模型的基础。元胞自动机提供了另一种方法。元胞自动机的广泛应用(在生物学、物理学、运筹学、社会学、计算机科学等领域)肯定会增加对这样一种工具的需求。基本的本构单元是离散的，非常适合用数字计算机模拟。它们只在局部环境中相互作用的特性自然导致了一种新的处理理念:细胞处理。事实上，用大型计算机模拟元胞自动机，即使使用并行多处理器，也总是因为输入/输出瓶颈而减慢速度。本文介绍了一种小型元胞自动机加速器的结构。这台多可扩展的机器是基于一个并行执行计算和显示结果的管道架构。其基本原理是通过抓取输出到显示设备的数据流来监视显示总线，同时评估网络中每个自动机的状态。机器性能达到视频速率:每秒24次计算并显示1024/spl次/1024次16位自动机的状态。fpga在系统架构中起着关键作用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Proceedings of IEEE Workshop on FPGA's for Custom Computing Machines

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