Abstract
Abstract A Cellular Automata (CA) model consists of a lattice of cells and a set of rules governing their behavior. Each cell holds one of a predetermined set of states such as dead or alive. CA are used to model the behavior of systems where many objects are reacting to each other. Modern CPUs and GPUs, however, are not designed to efficiently compute this type of model. In this paper, we proposed and implemented the CA called Conway’s Game of Life (CGoL) on a Field-Programmable Gate Array (FPGA) and compared it with previous implementations in literature such as optimized software solutions for General Purpose GPUs as well as previous FPGA implementations. Our experimental results show that an implementation of CGoL on even a basic FPGA allows for a speed gain of 36.7 times to that of a reference GPU implementation and 2,908 times that of an optimized software-based implementation.
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