EpsiloNN - A Specification Language for the Efficient Parallel Simulation of Neural Networks

. A neural network specification language is presented that can be used for the high-level description of artificial and biology-oriented neural networks. The main objective of the languagedesign is the support of the inherent parallelism of neural networks so that efficient simulation code for parallel computers and neurocomputer architectures can be generated automatically. In this paper the most important design aspects of the new language are described. Furthermore, the methodology for the efficient parallel code generation is illustrated. 1 Introduction Many scientific and engineering problems can be solved by simulating an appropriate neural network. However the learning phase of many neural network models is extremely computation-intensive because a large learning set must be presented to the network many times. The optimal neural network model for a given problem is also not known in advance. Many experiments with different neural network models, different network sizes..