In this article we discuss the flow of design for neural network hardware and go deeper into the design constraints and implementation possibilities. The performance measures and problems of different measurements are also discussed. It is noted that performance is one comparison criteria, but there are also many others, some of which are also discussed. In order to anchor the discussion to real life, the article includes a case study of our TUTNC neurocomputer. In addition, examples of commercial neural computing systems and their world wide web pages are given.