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It entails the use of computational methods (e.g., algorithms) for the representation and simulation of biological systems, as well as for the interpretation of experimental data, often on a very large scale.
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In previous work, we proposed the prototype environment SNet for the representation and dynamic simulation of agent-based designs for inter-organizational networks.
Most numerical simulations require techniques for the representation and manipulation of complex, three-dimensional geometries.
Languages for describing multi-level models are going to take more work and time because of the inherent complexity of the challenge, in terms of both representation and simulation.
We developed a transformation for the representation of non-branched workflows to concepts of an ontology that allowed a visual simulation of many common non-branched workflows of general practitioners.
Further, we present a collection of new techniques related to parallelism extraction, mapping of irregular communication, and network representation for effective simulation of SNNs on GPUs.
The minimal representation is used for optimization and the augmented representation for simulation, thereby keeping the simulator implementation unchanged.
The pilot implementation is using JADE multi agent platform and JGroups for real time data synchronization and NetLogo for abstract representation of the simulation system.
In addition to obtaining a simpler representation, the authors achieved savings on the computational load required for the simulation of the reduced model.
The graphical representation of the simulation is given in figure 10 and figure 11.
The paper considers only ASCII file representations of the finite element meshes, as this type of representation is usually available for all modeler and simulation software used by engineers.
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