The point being made is that in a production environment you cant't run/simulate all the possible candidate implementations to find out the fastest one -- it wo

The point being made is that in a production environment you cant't run/simulate all the possible candidate implementations to find out the fastest one -- it would take far longer than just choosing one at random. Therefore, you need an algorithmic way of picking a good candidate out of the many you have, and you can't take forever to make that selection either, because the clock is ticking the moment you receive a request to run that matrix multiply. You can't precompute all the possible options in advance and fetch the running time from a database either, because the parameter space is just way too huge. Notice that none of this has anything to do with having accurate models of the system. This is what people who do this for a living and have perfect knowledge of the system choose to do, for good reasons.