Visible to Intel only — GUID: GUID-25B5D553-708C-47E5-B7A2-F23D86D37F8B
Visible to Intel only — GUID: GUID-25B5D553-708C-47E5-B7A2-F23D86D37F8B
fprofile-ml-use
Enables the use of a pre-trained machine learning model to predict branch execution probabilities driving profile-guided optimizations.
Syntax
Linux: |
-fprofile-ml-use |
Windows: |
/fprofile-ml-use |
Arguments
None
Default
OFF |
The compiler follows default static heuristics for profile-guided optimizations. |
Description
This option enables the use of a pre-trained machine learning model to predict branch execution probabilities driving profile-guided optimizations.
It replaces the default static heuristics in the compiler and serves as a single-pass proxy to get the performance gains from the true 2-pass profiling methods by instrumentation/sampling.
This option only applies to host compilation. When offloading is enabled, it does not impact device-specific compilation.
IDE Equivalent
Visual Studio: DPC++ > Optimization > Use Pre-trained Machine Learning Model for Profile Guided Optimizations
C/C++ -> Optimization [Intel C++] > Use Pre-trained Machine Learning Model for Profile Guided Optimizations
Eclipse: Intel® oneAPI DPC++ Compiler > Optimization > Use Pre-trained Machine Learning Model for Profile Guided Optimizations (-fprofile-ml-use)
Intel C++ Compiler > Optimization > Use Pre-trained Machine Learning Model for Profile Guided Optimizations
Alternate Options
None
Examples
The following shows examples of using this option:
Linux
icx -c -fprofile-ml-use t.c
icpx -c -fprofile-ml-use t.cpp
Windows
icx /c /fprofile-ml-use t.c
icpx /c /fprofile-ml-use t.cpp