The processor must support the Intel(R) Streaming SIMD Extensions 4.2 (Intel(R) SSE4.2) instructions. The processor must support the Intel(R) Supplemental Streaming SIMD Extensions 3 (Intel(R) SSSE3) instructions. Intel MKL FATAL ERROR: This system does not meet the minimum requirements for use of the Intel(R) Math Kernel Library. Upon doing this I found issues with Intel MKL as per the error below: The solutions I found when searching on Google were primarily around forcing the Conda environment to use X86 versions of the dependencies assuming Rosetta2 emulation. As an unsafe, unsupported, undocumented workaround you can set the environment variable KMP_DUPLICATE_LIB_OK=TRUE to allow the program to continue to execute, but that may cause crashes or silently produce incorrect results. by avoiding static linking of the OpenMP runtime in any library. The best thing to do is to ensure that only a single OpenMP runtime is linked into the process, e.g. That is dangerous, since it can degrade performance or cause incorrect results. With a somewhat complex set of data science and database related dependencies (MatPlotLib, ScikitLearn, and PyTorch amongst others) I initially I came across this error:Įrror #15: Initializing libiomp5.dylib, but found libiomp5.dylib already initialized OMP: Hint: This means that multiple copies of the OpenMP runtime have been linked into the program. Problem: Intel Optimisations now break x86 emulation support for common Python data science libraries (PyTorch, MatplotLib, ScikitLearn) on newer M1 Apple Macs
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