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- W2155403248 abstract "The Kauman N-K, or random boolean network, model is an important tool for exploring the properties of large scale complex systems. There are computational challenges in simulating large networks with high connectivities. We describe some high-performance data structures and algorithms for implementing large-scale simulations of the random boolean network model using various storage types provided by the D programming language. We discuss the memory complexity of an optimised simulation code and present some measured properties of large networks." @default.
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- W2155403248 date "2007-01-01" @default.
- W2155403248 modified "2023-09-26" @default.
- W2155403248 title "Simulating Large Random Boolean Networks" @default.
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