Systolic artificial neural network prototyping using ptolemy
Theodore H. Kaskalis, Konstantinos G. Margaritis · International Journal of Computer Mathematics · 1998
In this paper we present an example of how the ptolemy environment can be used constructively to implement and simulate a certain class of Artificial Neural Networks, called Associative Memories. Through graphical means, the user can easily obtain prototypes in a level high enough to be comprehensive and, at the same time, low enough to present the design complexity of a potential implementation. Moreover, the ability to simulate the functioning of the circuit ensures the correctness of an algorithm. A brief introduction to the Ptolemy environment is given and a step by step creation of a typical systolic based Discrete Autocorrelator circuit is then described. A hierarchical design method is followed and details are given about the correct reflection of the synchronous nature of systolic circuits and the dynamic schedule imposed by iteration convergence on typical dataflow executions.