Paper on neural network simulation available

[Steve Lawrence]

It has been estimated that 85% of neural network researchers
write their own simulation software. The following paper deals
with correctness and efficiency in neural network simulation. 
We present several techniques which we have used in the 
implementation of our own simulator. We welcome your 
comments.


http://www.elec.uq.edu.au/~lawrence		- Australia
http://www.neci.nj.nec.com/homepages/lawrence	- USA


   Correctness, Efficiency, Extendability and Maintainability 
	  	 in Neural Network Simulation

 		         ABSTRACT

A large number of neural network simulators are publicly available to
researchers, many free of charge. However, when a new paradigm is
being developed, as is often the case, the advantages of using
existing simulators decrease, causing most researchers to write their
own software.  It has been estimated that 85% of neural network
researchers write their own simulators. We present techniques and
principles for the implementation of neural network simulators.  First
and foremost, we discuss methods for ensuring the correctness of
results - avoiding duplication, automating common tasks, using
assertions liberally, implementing reverse algorithms, employing
multiple algorithms for the same task, and using extensive
visualization.  Secondly, we discuss efficiency concerns, including
using appropriate granularity object-oriented programming, and
pre-computing information whenever possible.