Communications of the ACM
Efficient distributed event-driven simulations of multiple-loop networks
Communications of the ACM
Algorithms for Image Component Labeling on SIMD Mesh-Connected Computers
IEEE Transactions on Computers
Introduction to algorithms
Introduction to parallel algorithms and architectures: array, trees, hypercubes
Introduction to parallel algorithms and architectures: array, trees, hypercubes
Efficiency of data alignment on Maspar
ACM SIGPLAN Notices - Workshop on languages, compilers and run-time environments for distributed memory multiprocessors
TEMPEST: a fast spatially explicit model of ecological dynamics on parallel machines
Proceedings of the 1994 simulation multiconference on Grand challenges in computer simulation
Machine vision
Parallel algorithms for image histogramming and connected components with an experimental study
Journal of Parallel and Distributed Computing
Automatic optimization of communication in compiling out-of-core stencil codes
ICS '96 Proceedings of the 10th international conference on Supercomputing
High performance scientific computing by a parallel cellular environment
Future Generation Computer Systems - Special issue on HPCN96
Computer and Robot Vision
Special Report: 1989 Gordon Bell Prize
IEEE Software
Implementation and Performance of the Parallel Ecological Simulations
Proceedings of the IFIP WG10.3 Working Conference on Applications in Parallel and Distributed Computing
Theory of Self-Reproducing Automata
Theory of Self-Reproducing Automata
Fine-grain discrete Voronoi diagram algorithms in L1 and L∞ norms
Mathematical and Computer Modelling: An International Journal
Voronoi-like partition of lattice in cellular automata
Mathematical and Computer Modelling: An International Journal
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Cellular automata (CA) are fundamental computational models of spatial phenomena, in which space is represented by a discrete lattice of cells. Each cell concurrently interacts with its neighborhood which, in traditional CA, is limited to the cell's nearest neighbors. In this paper we discuss generalized cellular automata (GCA), an important but unexplored class of CA, in which the cell's interaction domain extends beyond the nearest neighbors. The computational power necessary to run large scale CA (and GCA) models has only recently been available thanks to parallel processing. This paper focuses on implementation and performance of GCA in biological modeling. In particular, we present results of simulating the spread of epidemics and the creation of spatial infection patterns that are important for disease control. The simulation system is implemented on three different platforms: the MasPar MP-1 SIMD computer, the IBM SP-2 MIMD machine and a network of workstations (NOW) that consists of Sun SPARCstation 5 and UltraSPARC 2's connected via Ethernet. The system presented in this paper has been specialized for simulating a four species spatially explicit model, however, the implementation may be readily modified to represent other models. Simulation results are presented for simple epidemics and vector-borne diseases spread by parasites.