Alfred Strey

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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 language design is the support of the inherent parallelism of neural networks so that efficient simulation code for parallel computers and neurocomputer architectures can be(More)
This paper presents a new concept for a parallel neurocom-puter architecture which is based on a conngurable neuroprocessor design. The neuroprocessor adapts its internal parallelism dynamically to the required data precision for achieving an optimal utilization of the available hardware resources. This is realized by encoding a variable number of p(More)
In this article the neural network speciication language EpsiloNN is presented. From an abstract speciication that is independent of the target computer architecture, a simulation source program for a workstation or a parallel computer can be generated. Neurocomputers requiring xed-point data types and arithmetic are supported too. The language design is(More)
A new methodology for the generation of efficient parallel programs from high-level neural network specifications is presented. All possible mappings of the neural network onto the parallel processors are generated and evaluated by using a description of the parallel target architecture. Thus the optimal mapping can be determined at compile-time and(More)