[phao]

He is mostly talking about computational linear algebra problems of a large scale type due to large matrices: the "computational intensity" comes from having really large matrices (kxk for k = 100's, 1 000's, 10 000's, 100 000's, 1 000 000's, ...).

In computer graphics, the situation is often different. Usually, you have small matrices (kxk for k=2,3,4); a huge number of vectors; and you want to apply your matrix to all of those vectors. Very often, these matrices have very well known forms and also known well behaved inverses. There isn't really a significant computational cost in computing the inverse (you'll very often write down its formula by hand), and conditioning is usually not an issue (consider a rotation matrix for example or undoing translations with homogeneous coordinates).

[bob1029]

Thank you for the clarification. I didn't realize we were talking about that kind of scale.