PARNEU : Scalable Multiprocessor System for Soft Computing Applications

Many soft computing applications have inherent parallelism in the form of synapses and neurons. Exploitation of parallelism will bring computers more close to their biological counterparts as well as improve the performance. Modularity and good communication capabilities are essential for practical implementations. Our multiprocessor system called PARNEU is designed according to general requirements found in artificial neural networks. PARNEU is a parallel co-processor system, which includes a bus, ring and reconfigurable partial tree communication networks. Programming is done using C-language primitives, which hide the communication topology. PARNEU is directly connected to the host computer, which includes a TCP/IP server for remote programming over Internet connection. Scalability of communication topology and artificial neural network applications, like Multilayer Perceptron (MLP), Self-Organizing Map (SOM) and Sparse Distributed Memory (SDM) are shown. Parallel efficiency with eight boards configuration is generally more than 75%.