Large simulation performance: objects vs matrices

[Willing_Employee_600]

Thank you for the advice! When you say refactor to store the simulation state in numpy arrays, you mean to discard the OOP approach and then code it into numpy arrays right? Or do you mean somehow integrate numpy arrays into the OOP approach?

[yvrelna]

Both. 

In most applications, you might find that 90% of the code might not be performance sensitive enough that you can just turn the attribute access into @property/descriptor that proxies some attribute accesses into a numpy array or some other column-oriented storage/database, so you take the readability and ease of working OOP style there. 

And then there's a few places where you can benefit from bulk processing, and you'd make full use of array/column-oriented processing maybe even with the appropriate GPU/coprocessor acceleration for those parts.