math kernel library function produce different result on different machine - fortran

Question

I'm implementing an eigen-decomposition method by making use of math kernel library in fortran.
Inside the method, I first try to apply zgehrd to convert the input matrix into a upper Hessenberg form.
During the debug, however, I found given the same input matrix, the method zgehrd produces different results on different computers. Some computers are in windows 10 while some are still in windows 7.
To further test whether this problem is system dependent, I installed a windows 10 (Pro 64 bit) VM machine on a windows 10 (Home 64 bit) computer. It turns out the results are still different slightly in this case.
Since the eigen-decomposition method will be recursively called by an optimizer, the slight differences will accumulate. I've tried the solution by enforcing the Conditional Numerical Reproducibility in fortran, yet it does not help. Any help would be appreciated

Answer 1

if you want to see bit-to-bit output results with Intel MKL on different machines, please call MKL_VERBOSE mode ( set/export environment variables MKL_VERBOSE=1 ) first and check the lowest reported code branch. Example:
running the MKL code on AVX and AVX-512 based systems we will see the following messages:
MKL_VERBOSE Intel(R) MKL 2019.0 Update 4 Product build 20190411 for Intel(R) 64 architecture Intel(R) Advanced Vector Extensions (**Intel(R) AVX**) enabled processors, Lnx 2.80GHz intel_thread
and on SkyLake system:
MKL_VERBOSE Intel(R) MKL 2019.0 Update 4 Product build 20190411 for Intel(R) 64 architecture Intel(R) Advanced Vector Extensions 512 (**Intel(R) AVX-512**) enabled processors, Lnx 2.20GHz intel_thread
The next steps:
Calling the MKL’s bitwise reproducibility features by setting the environment variables: set/export MKL_CBWR=AVX
Then MKL guarantees that you will see the same outputs on AVX and AVX-512 based systems in the case of the same #of threads and the same OS.