A parallel processor for neural networks

We present two different algorithms implemented through neural networks on a multiprocessor device. The parallel single-chip TI TMS32C80 Multimedia Video Processor (MVP). The goal of this experimentation is to test, on real problems, the performance of this powerful unit made up by one Master Risc Processor and by four Slave Digital Signal Processors (DSPs) and to evaluate its suitability to neural network applications. The first problem implemented is a typical classification algorithm in which the network recognises which points belong to different regions inside a 2D space. The second problem is more computationally heavy and consists of a network able to recognise `handwritten´ digits. The parallel version of the first algorithm, was also tested on a commercially available supercomputer