I'm doing a bundle adjustment using posv to solve the system and potri for the covariance matrix. I use very big symmetric matrices ( > 20,000x20,000) so the calculation takes some time. The bundle adjustment is a refining process; some iterations followed by stat check accuracy forms a pass. There are mostly more than one pass for each dataset.
I recorded the time it takes for some processes (iteration, pass, solving, inversion) and I had some strange results. For small datasets (matrices smaller than 10,000), everything is ok; with the MKL library, it is very fast. :) However, with bigger ones, the time is unpredictable: be itabout computation time (MKL library) and initialisation time(program design). Doesthe computation timedepend of the exact size of the matrix, like being a multiple of 2 (which is MKL related "issue")? I read something about it in the User Manual (p. 6-14), but I wasn't sure if it applies to my problem.
I'm not familiar with the reference about multiples of 2. There is a reference about choosing sizes such that each row or column is 16-byte aligned; that should have most effect on problems much smaller than yours, while the suggestion about what fits in RAM is rightly given for larger problems.