Micro-Optimization

Over the last year, as a person with a hardware background, I have heard a lot of complaints about Nvidia’s dominance of the machine learning market and whether I can build chips to make the situation better. While the amount of money I would expect it to take is less than $7 trillion, hardware accelerating this wave of AI will be a very tough problem–much tougher than the last wave focused on CNNs–and there is a good reason that Nvidia has become the leader in this field with few competitors.

A modern CPU is an incredible machine. It can execute many instructions at the same time, it can re-order instructions to ensure that memory accesses and dependency chains don’t impact performance too much, it contains hundreds of registers, and it has huge areas of silicon devoted to predicting which branches your code will take. However, if you have a tight loop and you are interested in optimizing the hell out of it, the same mechanisms that make your code run fast can make your job very difficult.