Model Application Performance on a Custom Target GPU Device
You can change GPU parameters to model performance of future or custom graphics processing units (GPU) and see how your application performance changes.
Intel® Advisor
has several predefined GPU device configurations that you can use to model application performance. If you want to estimate performance on a future GPU device or experiment with hardware parameters to see how they can change application performance, you can modify target hardware parameters for the
Offload Modeling
perspective in one of the following ways:
- Customize hardware parameters using sliders in aninteractive remodeling panein theIntel Advisorgraphical user interface (GUI) or an interactive HTML report and remodel performance. This is currently available for GPU-to-GPU modeling only.
- Generate a TOML configuration file that defines customized hardware parameters and use the file to remodel performance withIntel Advisorcommand line interface (CLI). You can generate the file using the interactive modeling pane in theIntel AdvisorGUI or the interactive HTML report. You can reuse the file for multiple analysis executions.
- Provide a command-line option with one or more modified target hardware parameters when running the analysis withIntel AdvisorCLI. This is a one-time change.
Use the Modeling Parameters Pane
When you open the
Summary
tab of the
Offload Modeling
report in the
Intel Advisor
GUI or the
interactive HTML report, you should see the
Modeling Parameters
pane, which shows the current modeled device and its parameters. Each parameter is a slider you can move to change its value.

You can use this pane to:
- Examine device parameters that the application performance was modeled on to understand how they affect the estimated performance.
- Change the target device to compare the new configuration with the current modeled device.
- Adjust the parameters and remodel performance for a custom device. You can experiment with parameters to see how they affect the application performance or adjust the configuration to model performance for a future or a specific device not listed in the target devices. See the sections below for a full workflow.For CPU-to-GPU modeling, you can remodel performance usingIntel AdvisorCLI only.
For details about pane controls. see
Window: Offload Modeling Summary.
The parameter list might change depending on the target device selected. This might be due to differences between GPU architecture or terminology specifics. For example, the
Gen11 GT2
configuration has the LLC bandwidth and LLC size parameters, while the
XeLP Max 96
does not because of architecture differences.
Families of Intel® X
e
graphics products starting with Intel® Arc™ Alchemist (formerly DG2) and newer generations feature GPU architecture terminology that shifts from legacy terms. For more information on the terminology changes and to understand their mapping with legacy content, see
GPU Architecture Terminology for Intel® Xe
Graphics.
Remodel Performance from GUI
This workflow is currently available for remodeling from a baseline GPU to a different target GPU device using
Intel Advisor
GUI. You can remodel application performance for the custom device from the
Offload Modeling
report.
Prerequisites:
- Set up system to analyze GPU kernels.
- RunOffload Modelingwith your preferred method: from graphical user interface or from command line interface.
- Open the result in theIntel AdvisorGUI.
To customize the hardware parameters and remodel application performance:
- In theAnalysis Workflowpane, make sureGPUdevice is selected in theBaseline Devicedrop-down.
- Optional: In theModeling Parameterspane of the Summary report, select a device from theTarget Devicedrop-down to use as a baseline for further changes.If you do not change the device, the current modeled target device will be used a baseline.
- Move the sliders underHardware Parametersto the desired values. The black line indicates the baseline parameter value, and the blue line indicates the difference between the new value and the baseline value.For example, you can increase the number of execution unitsEU Countto enable more compute operations to be executed at once. This can be useful for compute-bound applications, which is indicated in theOffload Bounded Bypane.
- Click
button at the top of the pane to run the Performance Modeling analysis for your target device configuration.
When the analysis execution completes, the result estimated for the custom device configuration opens. - Examine the performance changes for the new target GPU.For example, if you increased the EU count value, you may see the compute time and compute bound percentage decreased and compute estimate metrics changed.
Remodel Performance Using a Configuration File
This workflow is currently available for remodeling performance:
- From a baseline CPU to a custom GPU using Intel Advisor GUI or an interactive HTML report
- From a baseline GPU to a custom GPU using an interactive HTML report
For these cases, you can modify the parameters using
Offload Modeling
report and remodel performance using
Intel Advisor
CLI only.
Prerequisites:
- RunOffload Modelingwith your preferred method: from graphical user interface or from command line interface.
- Open the result in theIntel AdvisorGUI on an interactive HTML report.
To customize the hardware parameters and remodel application performance:
- Optional: In theModeling Parameterspane of the Summary report, select a device from theTarget Devicedrop-down to use as a baseline for further changes.If you do not change the device, the current modeled target device will be used a baseline.
- Move the sliders underHardware Parametersto the desired values. The black line indicates the baseline parameter value, and the blue line indicates the difference between the new value and the baseline value.For example, you can increase the number of execution unitsEU Countto enable more compute operations to be executed at once. This can be useful for compute-bound applications, which is indicated in theOffload Bounded Bypane.After you move a slider, theSave to Remodelbutton activates, enabling you to save your custom configuration.Currently, for the CPU-to-GPU modeling, if you change the memory-related parameters, such as bandwidth or size, run the Characterization analysisfirstwith Trip Counts and multi-device cache simulation (for CLI, run Trip Counts collection with--cache-simulation=multioption)beforerunning the Performance Modeling with the custom configuration. Otherwise, the results may not be accurate because they require updating cache simulation for the new device.
- ClickSave to Remodelto save the generated configuration file.TheSave Configurationdialog box opens.
- In the opened dialog box, navigate to a location to save the TOML file, change the file name if needed, and clickSave. By default, the file is saved asconfig.toml.After you save the custom configuration file, a command line for the Performance Modeling analysis appears under the hardware parameter sliders in theModeling Parameterspane.
- Click
to copy the command line generated under the hardware parameters to a clipboard.
Notice that the command line has a option with a full path to the custom configuration file you saved. The command line has all required options, and you can copy and paste it without modifications. - Paste the copied command to a terminal or a command prompt and run it.After the analysis execution completes, the result in your project directory will be updated for the new target device configuration.
- Open the updated results with your preferred method and examine the performance changes for the new target GPU.For example, if you increased the EU count value, it you may see the compute time and compute bound percentage decreased and compute estimate metrics changed.
Remodel Performance Using a Command Line Option
When you run the Offload Modeling perspective from the command line, you can use the
--set-parameter=<parameter-to-change>
option to change target parameters. You can use this option with the Offload Modeling collection preset or the Performance Modeling analysis. This is a one-time change applied only for the current execution. You can specify more than one parameter as a comma-separated list.
For example, you can model performance for a target device with 1.4 GHz frequency, 224 execution units, and other parameters corresponding to the
gen12_tgl
device configuration as following:
advisor --collect=offload --config=gen12_tgl --set-parameter="EU_count=224,Frequency=1.4e+9" --project-dir=./advi_results -- ./myApplication
You can open the generated results with your preferred method and examine the performance changes for the new target GPU.
To see what parameters you can change, you can save a configuration file for a selected device from Intel Advisor GUI or HTML report and examine the parameters listed.