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The original goal was to build the inference engine and the plugins (specifically MKLDNNPlugin) from the sources in Github using the additional compilation flags (DAZ and FTZ enabled). I have previously built these dlls on my end, and it was not a simple process. Several small changes needed to be made in the source files to get it to build successfully, and eventually, the inference engine did not behave the same as the official version. We assume the differences are due to different compilers or different compilation flags.
So, instead of spending any more days/weeks trying to figure out the cause for the different behavior, we thought it would be simpler to ask you to generate a version of the inference engine dlls built with the additional compilation flags. The only purpose is to see how preventing denormalization affects the inference run time. If we find this significantly reduces the inference run time without changing the accuracy of the results, it could be beneficial for Intel to build the official release versions with these flags as well.
I hope it is clearer now and that you are able to provide this kind of assistance.
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Hi Yaniva,
Thanks for reaching out to us.
We are checking with our development team to further assess this request, and shall get back to you once we’ve obtained feedback from them.
Regards,
Munesh
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Hi Yaniva,
Apologies for the delay in replying to you.
Glad to inform that your feature request has been enabled, and you can perform denormals optimization during inferencing using OpenVINO 2022.2. For more information, please refer to Intel CPU specific properties
We deeply appreciate your patience and understanding during this feature request enablement period.
Regards,
Munesh
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Hi Yaniva,
This thread will no longer be monitored since we have provided a solution. If you need any additional information from Intel, please submit a new question.
Regards,
Munesh

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