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Three Big Lies - CellPerformance

This is a repost of a blog entry I wrote for the Insomniac R&D site (

Three Big Lies

). It's representative of what I believe are some of the fundamental problems in the culture of software development in general, and games in particular. There are some fundamental truths that seem to be often forgotten. For example, that the point of any program is simply to transform data from one form into another and nothing else. And as one "solution" which ignores the real core problems of development is developed and others over time are built on top of that idea, and so on, we're left with systems that are over-designed, perform poorly and simply do not accomplish what they intended to in the first place - and certainly not well. I continue to suggest that we all take a step back from what we're doing and the methods we're using to solve problems and try to remember what the real issues are.

One of the things we talked about this year at GDC was what we called the "Three Big Lies of Software Development." How much programmers buy into these "lies" has a pretty profound effect on the design (and performance!) of an engine, or any high-performance embedded system for that matter.

(Lie #1) Software is a platform

I blame the universities for this one. Academics like to remove as many variables from a problem as possible and try to solve things under "ideal" or completely general conditions. It's like old physicist jokes that go "We have made several simplifying assumptions... first, let each horse be a perfect rolling sphere..."

The reality is software is not a platform. You can't idealize the hardware. And the constants in the "Big-O notation" that are so often ignored, are often the parts that actually matter in reality (for example, memory performance.) You can't judge code in a vacuum. Hardware impacts data design. Data design impacts code choices. If you forget that, you have something that might work, but you aren't going to know if it's going to work well on the platform you're working with, with the data you actually have.

(Lie #2) Code should be designed around a model of the world

There is no value in code being some kind of model or map of an imaginary world. I don't know why this one is so compelling for some programmers, but it is extremely popular. If there's a rocket in the game, rest assured that there is a "Rocket" class (Assuming the code is C++) which contains data for exactly one rocket and does rockety stuff. With no regard at all for what data tranformation is really being done, or for the layout of the data. Or for that matter, without the basic understanding that where there's one thing, there's probably more than one.

Though there are a lot of performance penalties for this kind of design, the most significant one is that it doesn't scale. At all. One hundred rockets costs one hundred times as much as one rocket. And it's extremely likely it costs even more than that! Even to a non-programmer, that shouldn't make any sense. Economy of scale. If you have more of something, it should get cheaper, not more expensive. And the way to do that is to design the data properly and group things by similar transformations.

(Lie #3) Code is more important than data

This is the biggest lie of all. Programmers have spent untold billions of man-years writing about code, how to write it faster, better, prettier, etc. and at the end of the day, it's not that significant. Code is ephimiral and has no real intrinsic value. The algorithms certainly do, sure. But the code itself isn't worth all this time (and shelf space! - have you seen how many books there are on UML diagrams?). The code, the performance and the features hinge on one thing - the data. Bad data equals slow and crappy application. Writing a good engine means first and formost, understanding the data.

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