All the GIL examples I saw use iterators and what I liked is that complicated image calculations can be stacked. If I have to flip the an image and convert it to B/W then traditionally I would do that in two steps, with Gil you do that in one step only, with nearly double performance.
I was going to reply earlier but since you touched on the issues I wanted to mention, let me just suggest that cache awareness be considered as a null inner loops has no obvious performance relationship to something that just writes a constant into incrementing addresses. Any iterator that preserves locality and anything that reduces the number of "passes" can easily pay for some overhead, especially of order zero ( some setup calculations that determine things like block sizes etc but don't get repeated during iteration). I don't have links handy but I think that FFTW has a lot of related literature on performanc issues and, again, Intel has a lot of good optimization references on their site for their processors.
Are there performance measurements for GIL?
GIL uses Locators, which I love. GIL seems to be stuck on arrays that are an 'image' of 'pixels', which is not always the case for me. Ideally I would be able to construct an array of any type.
I was looking into multi_array hoping there would be some analogy to GIL / Locators, but multi_array seems to be mimicking aspects of the syntax used in Fortran, Matlab, or Python. That's great from a high level point of view, but I am a bit afraid because I don't understand the performance implications.
I think that in the spirit of 'zero overhead', there should be some boost requirement that certain libraries include performance measurements / graphs as part of their docs or build process. For things like multi_array or uBLAS or GIL, I think efficiency is important (not just asymptotic).
For example, I would feel more comfortable if I could see something like: http://www.oonumerics.org/blitz/benchmarks/
(The only reason I don't wanna use BLITZ is that the last release was 2005)
--John
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