[GitHub] [incubator-mxnet] mozga-intel edited a comment on pull request #20474: [FEATURE] Enable dynamic linking with MKL and compiler based OpenMP

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mozga-intel edited a comment on pull request #20474:
URL: https://github.com/apache/incubator-mxnet/pull/20474#issuecomment-904390250


   > > Hi @akarbown It looks really good. Thanks! I have a question.
   > > Basically, there are two ways: either we'll use MKL_THREADING_GNU or MKL_THREADING_INTEL. Could you please tell me whether there are differences in performance results, or, there is no impact on that?
   > 
   > @mozga-intel, this boils down to comparison between ICX and GCC compilers. The whole point of this PR is mainly to enable using dynamic linking of MKL libraries without hang or different OpenMP symbol conflicts. Thus performance of this 2 compilers is not really an issue here. Unit tests for both compilers run more or less in the same time (on my local machine). I've observed 10 more tests failures for icx than for gcc (unittest_ubuntu_python3_cpu), but it seems to be because of the fact that it wasn't tested before and there were problem with compiling MxNET with icc at all.
   
   Thanks, Anna! I have one more question: it might not exactly aim at an issue like this. Please have a look at the scenario like this: If I have huge matrices then I can use one of those functionalities: either sparse or dense BLAS. 
   If I try to use the IIL64 interface for huge matrices on a 32-bit architecture, will I get either an error message or everything is okay? (...) 32-bits architecture doesn't support the ILP64 interface, and LP64 works only for a small tensor. Could be possible that it works for dense matrices but for a sparse I will get an error? Or, maybe the matrices will be divided into small matrices [?]
   


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