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Measures reported by WVDGPUAppTest
GPU-accelerated computing is the use of a graphics processing unit (GPU) together with a CPU to accelerate scientific, analytics, engineering, consumer, and enterprise applications. GPU-accelerated computing enhances application performance by offloading compute-intensive portions of the application to the GPU, while the remainder of the code still runs on the CPU.
In GPU-enabled AVD environments, if users accessing graphic virtual applications complain of slowness , administrators must be able to instantly figure out what is causing the slowness – is it because adequate GPU resources are not available to the host? Or is it because of excessive utilization of GPU memory and processing resources by a few virtual applications on the host? Accurate answers to these questions can help administrators determine whether/not:
- The host is sized with sufficient GPU resources;
- The GPUs are configured with enough graphics memory;
Measures to right-size the host and fine-tune its GPU configuration can be initiated based on the results of this analysis. This is exactly what the WVDGPUAppTest test helps administrators achieve!
To help with better utilization of resources, you can track the GPU usage rates of your instances. When you know the GPU usage rates, you can then perform tasks such as setting up managed instance groups that can be used to autoscale resources based on needs.
Outputs of the test : One set of results for each application on the chosen Session Host / Azure Virtual Desktop that is using GPU.
The measures made by this test are as follows:
| Measurement |
Description |
Measurement Unit |
Interpretation |
| No_of_gpu_processes |
Indicates the number of instances of this graphic application that are currently running. |
Number |
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| GPU_utilization |
Indicates the percentage of time for which this application was utilizing GPU. |
Percent |
A value close to 100% indicates that the GPU is busy processing graphic requests from this application almost all the time.
In such a case, you may want to consider allocating more GPU resources to that AVD. |
| Encoder_utilization |
Indicates the amount of GPU that this application is utilizing for the encoding process. |
Percent |
A value close to 100 is a cause of concern. By closely analyzing these measures, administrators can easily be alerted to situations where graphics processing is a bottleneck. |
| Decoder_utilization |
Indicates the amount of GPU that this application is utilizing for the decoding process. |
Percent |
| Memory_utilization |
Indicates the percentage of time during which memory on the GPU was read from/written to by this application. |
Percent |
A value close to 100% is a cause for concern as it indicates that the application is almost always using the graphics memory on a GPU.
In such a case, you may want to consider allocating more graphics memory to that AVD. |
| Memory_in_use |
Indicates the amount of graphics memory used by this application. |
MiB |
Compare the value of this measure across applications to know which application is hogging GPU memory. |
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