Intel® Advisor Help

Check for Dependency Issues

Accuracy Level

High

Enabled Analyses

Survey + Characterization (Trip Counts and FLOP with cache simulation and medium data transfer simulation) + Dependencies + Performance Modeling

Result Interpretation

Without the Dependencies analysis, if a loop is not explicitly marked as parallel with pragmas or if a compiler assumes dependencies present, Intel® Advisor assumes the loop is not recommended for offloading because they have high compute time. In this case, you can see high percentage of dependency-bound code regions. To get accurate information about dependencies, run the Dependencies analysis.

After running the Offload Modeling perspective with High accuracy, you will get a complete Offload Modeling report extended with detailed information about loops that have and do not have dependencies and a full data transfer report.

If you had a report generated for a lower accuracy, all offload recommendations, metrics, and speedup will be updated to be more precise taking into account new data.

Note

This topic describes data as it is shown in the Offload Modeling report in the Intel Advisor GUI and an interactive HTML report.

Example of an Accelerated Regions report with data dependencies (Offload Modeling perspective)

In the metrics table of the Accelerated Regions tab:

Review the Data Transfer Estimations pane with detailed information about data transferred between host and device and memory objects. In addition to basic data transfer report, it includes:

Get guidance for offloading your code to a target device and optimizing it so that your code benefits the most in the Recommendations tab. If the code region has room for optimization or underutilizes the capacity of the target device, Intel Advisor provides you with hints and code snippets that may be helpful to you for further code improvement.

Next Steps

If you think that the estimated speedup is enough and the application is ready to be offloded, rewrite your code to offload profitable code regions to a target platform and measure performance of GPU kernels with GPU Roofline Insights perspective.

See Also