Intel® Advisor Help
A code region of interest is not analyzed and has Outside of Marked Regionwhy-not-offloaded message in the Details pane of the Accelerated Regions tab after you execute the Offload Modeling perspective.
To limit the scope of collections, the Intel® Advisor selects loops that match certain criteria and marks them up for analysis. By default, the Intel Advisor performs a smart region selection using the generic markup.
If a code region does not satisfy the markup criteria, you should see the Outside of Marked Regionwhy-not-offloaded message or the System Modulediagnostics message in the Details pane of the Accelerated Regions tab.
Your code region does not satisfy one or more markup rules for a specified markup mode. If you use the default generic mark-up strategy, make sure your loop of interest satisfies the following rules:
It is not a system module or a system function.
It has instruction mixes.
It is executed.
Its execution time is not less than 0.02 seconds, which is a sampling interval of the Intel Advisor. For more information about execution time limitations, see Total Time is Too Small for Reliable Modeling.
If a code region does not satisfy the generic markup rules, but you want to analyze it, do one of the following:
You can change the markup strategy by using a --markup=<markup_mode> option of analyze.py or --select markup=<markup-mode> for --collect=performance. The following parameters select only loops inside regions that are already parallel:
generic or gpu_generic (default) - Select loops executed on a GPU.
omp - Select loops only in OpenMP parallel regions.
dpcpp - Select loops only in Data Parallel C++ parallel regions.
daal - Select loops only in Intel® oneAPI Data Analytics Library parallel regions.
tbb - Select loops only in Intel® oneAPI Threading Building Blocks parallel regions.
omp, dpcpp, and generic/gpu_generic select loops in the project so you can run another collection or performance modeling without markup or loop selection options.
If your loops of interest are not marked up because they have no static instruction mixes or not executed, you can limit the analysis to these specific loops by using the --select-loops option with the analyze.py script. With this option, only the loops specified are analyzed. For example:
advisor-python <APM>/analyze.py <project-dir> --select-loops=[<file-name1>:<line-number1>,<file-name1>:<line-number2>,<file-name2>:<line-number3>]
With --collect=performance, use --select option to select specific loops to analyze by source location, ID, or other criteria.