INTRODUCTION
I think the true power of Houdini is that it allows an artist to solve technical problems and leverage technical processes to make beautiful things and solve complex problems from a high level.
As we connect nodes, write VEX in wrangles or wire Vops together, we are creating a set of instructions or rules, that given a set of inputs - for example geometry data or user input - output a result.
These sets of rules and processes are algorithms. An algorithm is an umbrella term used to describe any process or set of rules that can be followed - usually a computer.
This reality can feel distant as we work in Houdini’s environment concentrating on aesthetics and solving our problems, but to think of our graph of nodes and lines of VEX as algorithms can help us improve our workflow, setups and productivity.
Sometimes we create an algorithm that has the desired output when given a valid input. However, it may not always do it at the appropriate scale, within an acceptable time, or within the available machine resources.
In other words our algorithm needs to:
Sufficiently scale. For example, if your algorithm makes procedural rocs, it needs to be able to create geometry of a certain density to hold up.
Evaluate fast enough. For example, if an artist needs fast feedback in order to interact fluently with it, an Artist will not be able to use it effectively if it takes too long to reevaluate or cook.
Do it within the available machine resources. If your algorithm cannot stay within a machine's resources whilst evaluating, it will frequently overwhelm the machine causing work to come to a halt.
In this article I outline my process of how I prepare and optimise my algorithms in Houdini to hit performance requirements. Although written from the perspective of an artist/TD working in Houdini within the Sop context, most principles should apply to Houdin’s other contexts, and broadly it should be useful in creating algorithms in other software or programming languages. Click the button to read on.
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