since I can run now the mkl library 2017, I have a couple of follow up questions that hopefully deserve a thread of their own. I am doing some mode matching, and consequently I need matrix inversions on matrices of the order 10x10 up to 50x50 most of the time (the maximum size would be somewhere aroud 200x200 but very rarely, they will almost exclusively be in the 10-50 range). I have optimized my non mkl parts of the code so they are under 10% of all the simulation time, so any speedup on the mkl functions would be greatly beneficial, if possible. Now I have set the mkl_num_threads to max, release mode, ia32, O2 optimization, optimized for speed and so forth to make it as fast as I can/know to make currently. I only have a couple of matrices to invert per frequency point (5 to 6), and the code must execute one frequency point at a time. My questions are as follows:
1) Is there a way to improve the performance of the mkl functions in any way (by setting some flags in the program itself, or in Visual studio, or am I missing some functions that are better in this situation, or something else completely), either in the mkl 2017 or the old mkl 10.0.012 that I have? I am using cblas_zgemm, cblas_zdscal, zgetri, zgetrf, vzSqrt, cblas_zaxpy, but most of the time is spent in matrix inversion, so zgetri, zgetrf take most of the time. Are there better functions than these or can I set some additional flags to make them faster?
2) Since the optimization is for speed and not size, I of course expected the output (exe) to be bigger, but can someone explain and/or help me optimize the output size for the exe in mkl 2017, because it is 3x bigger than with the old mkl 10.0.012? This represents a small problem unfortunatelly, and if possible I would be very happy if it can be mittigated in any way (without optimize for size)
3) Some of the matrices are symmetrical, and I was hopping that the symmetrical versions of zgetri, zgetrf, that is zsytrf and zsytri, I would be able to theoretically get a 2x speedup, but for some reason the speed is the same. Is this expected? Are my matrices too small for any noticeable effect? Am I missing something? In both cases I feed the functions the full matrix to invert, and while I am debugging I can see that only half of the matrix elements are calculated for the symmetrical functions, and I fill the symmetric elements, but there is no speed up.
Any information, even if not good is welcome. Thank you all in advance.