Global Cellular Automata GCA -- A Massively Parallel Computing Model
Rolf Hoffmann

TL;DR
The paper introduces the Global Cellular Automata (GCA) model, a massively parallel computing framework with dynamic global neighborhoods, enabling efficient data parallel applications and transformations of PRAM algorithms.
Contribution
It generalizes classical cellular automata to include global, variable neighborhoods, and discusses its implementation, applications, and relation to PRAM models.
Findings
GCA allows parallel updates without conflicts.
GCA can implement many PRAM algorithms.
GCA is suitable for hardware and software implementations.
Abstract
The Global Cellular Automata (GCA) Model is a generalization of the Cellular Automata (CA) Model. The GCA model consists of a collection of cells which change their states depending on the states of their neighbors, like in the classical CA model. In generalization of the CA model, the neighbors are no longer fixed and local, they are variable and global. In the basic GCA model, a cell is structured into a data part and a pointer part. The pointer part consists of several pointers that hold addresses to global neighbors. The data rule defines the new data state, and the pointer rule define the new pointer states. The cell's state is synchronously or asynchronously updated using the new data and new pointer states. Thereby the global neighbors can be changed from generation to generation. Similar to the CA model, only the own cell's state is modified. Thereby write conflicts cannot…
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Taxonomy
TopicsCellular Automata and Applications · Quantum-Dot Cellular Automata · Coding theory and cryptography
