Computer science courses these days do in fact teach about memory coherency and MESI protocols with respect to CPU cache management and architecture. You'd lear

Computer science courses these days do in fact teach about memory coherency and MESI protocols with respect to CPU cache management and architecture. You'd learn about pipelining as well, and scalar architectures for that matter. I guess my point is that even if you didn't, if you wanted a head start, it's sufficient to know at least the basics of what microarchitectures are, and how to reason about a computational model of complexity, even if you need to adjust it later (for a particular console, or GPU, or architecture). As for quaternions, I can derive them (no really, I've written a ton of code in this space, although I prefer the GA formulation), but I want to know, does the candidate understand why they're mathematically advantageous (blending properties, linearity, etc). Can they productively read a paper that uses it and apply the technique, etc.