Branch and Bound, Structured Grids, and Graphical Models

It is nice to see some discussion of graphical processing, and it makes sense then that what we would see is a whole-picture processing by effect on the image. Also, what's with that particular image being some sort of academic standard. It seems... sleazy.

Anyway. I find it strange that the Structural Grid pattern (perfect for that sort of application as is indicated in the paper) starts out presenting itself as though it is going to be a discussion of a multidimensional version of the multicore array we discussed earlier and then begins to try to phrase itself as some sort of master conductor unit when it is clearly exactly a tool to help apply basic operations over multiple dimensions quickly. Multiple threads are of course going to be needed for that to work, and the data structure should be the one to dispatch but I kept reading the phrasing as though it was overstating what was actually being accomplished. The discussion on the ghost nodes would have benefited from a little more depth and a few more examples. Other than that a good description of what was necessary.

I liked the amount of coverage of the different approach styles in the Branch & Bound paper and the description of the pros and cons of each. I also appreciated a concrete example of when the multiqueue structure would be used to gain efficiency, and the fact that the queue technique in the previous paper was used directly. It seems to me that using the branch and bound technique to drive statistical models (like the problems Monte-Carlo is being used for in most examples) would be a viable route as we can limit the total number of runs using this structure and then collapse the results to find the actual best and the conditions under which it occurs.