GPU Adapter Details - OS Test

A graphics processing unit (GPU) adapter (also known as video card, graphics card, and video adapter) is a discreet card connected to one or more physical/physical machines. The GPU adapter contains video RAM and a GPU chip and renders real-time 2D and 3D graphics applications, images, animations and video by performing rapid mathematical calculations. To perform such calculations at higher speed, the GPU adapter should be allocated with adequate memory on the desktop. Inadequate memory allocation and inefficient utilization of the GPU adapter can affect the processing of intensive tasks related graphics on the desktops, which in turn can adversely impact the performance of the applications operating on the desktops. Therefore, it is imperative that administrators should closely observe how well the GPU adapter uses the allocated and shared memory available to it. This way, a potential memory crunch can be proactively detected. This can be achieved with the help of the GPU Adapter Details - OS test.

The test auto-discovers the GPU adapters connected to each virtual desktop on a cloud server and for each GPU adapter, reports the statistics related to memory utilization. This test also reveals how well the GPU is utilized for performing different tasks such as video decoding, processing 3D frames, etc. These metrics help administrators to judge whether/not adequate memory is available for use by the GPU adapters and identify the GPU adapter that is running out of memory.

Target of the Test: An Amazon Cloud Desktop Group

Agent deploying the test : A remote agent

Outputs of the test : One set of results for every combination of each desktop:GPU adapter

Configurable parameters for the test
Parameter	Description
Test Period	How often should the test be executed.
Host	The nick name of the Amazon Cloud Desktop Group component for which this test is to be configured.
Port	Refers to the port at which the specified host listens to. By default, this is NULL.
Inside View Using	To obtain the 'inside view' of performance of the desktops - i.e., to measure the internal performance of the cloud-based virtual desktops - this test uses a light-weight eG VM Agent software deployed on each of the desktops. Accordingly, this parameter is by default set to eG VM Agent.
Report Powered OS	If this flag is set to Yes (which is the default setting), then the 'inside view' tests will report measures for even those desktops that do not have any users logged in currently. Such desktops will be identified by their name and not by the username_on_desktopname. On the other hand, if this flag is set to No, then this test will not report measures for those desktops to which no users are logged in currently.
Report By User	This flag is set to Yes by default. The value of this flag cannot be changed. This implies that the cloud-based virtual desktops in environments will always be identified using the login name of the user. In other words, in cloud environments, this test will, by default, report measures for every username_on_desktopname.
IsCloudVMs	Since this test runs for a 'Amazon Cloud Desktop Group' component, this flag is set to Yes, by default.
Detailed Diagnosis	To make diagnosis more efficient and accurate, the eG Enterprise embeds an optional detailed diagnostic capability. With this capability, the eG agents can be configured to run detailed, more elaborate tests as and when specific problems are detected. To enable the detailed diagnosis capability of this test for a particular server, choose the On option. To disable the capability, click on the Off option. The option to selectively enable/disable the detailed diagnosis capability will be available only if the following conditions are fulfilled: The eG manager license should allow the detailed diagnosis capability Both the normal and abnormal frequencies configured for the detailed diagnosis measures should not be 0.

Measurements made by the test
Measurement	Description	Measurement Unit	Interpretation
Available GPU memory	Indicates the total amount of memory allocated for this GPU adapter on this desktop.	MB
GPU memory used	Indicates the amount of memory that is utilized by this GPU adapters.	MB
GPU memory free	Indicates the amount of memory that is available for use by this GPU adapter.	MB	Ideally, the value of this measure should be high. A consistent decrease in the value of this measure is indicative of a steady erosion of memory available for GPU, which if left unattended, can significantly impact GPU functioning.
GPU memory usage	Indicates the percentage of memory that is utilized by this GPU adapter.	Percent	A low value is desired for this measure. If the value of this measure grows very close to 100%, it indicates that the GPU will soon run out of memory resources. Such an occurrence will not only impact the functioning of the GPU card, but also the applications depend on it.
Total dedicated video memory	Indicates the total amount of dedicated video memory allocated this GPU adapter.	MB	The dedicated video memory or Video RAM (or VRAM) is a special type of RAM that works with your computer's GPU card/adapter. The video RAM holds information that the GPU needs, including game textures and lighting effects. This allows the GPU to quickly access the info and output video to your monitor.
Used dedicated video memory	Indicates the amount of dedicated video memory that is utilized by this GPU adapter.	MB	Ideally, a low value is desired for this measure. A high value for this measure indicates that the dedicated video memory is depleting rapidly. When the dedicated video memory is filled up, the GPU will rely on standard RAM for processing video frames and display textures. This in turn will seriously impact overall performance of the RAM.
Free dedicated video memory	Indicates the amount of dedicated video memory that is available for use by this GPU adapter.	MB	A high value is desired for this measure. If the value of this measure is very low, it indicates that the GPU does not have adequate memory for processing video frames.
Dedicated memory usage	Indicates the percent of dedicated video memory that is utilized by this GPU adapter.	Percent	Use the detailed diagnosis of this measure to find out the names of top-10 applications that are over-utilizing the dedicated memory. Administrators can also find out the percentage of dedicated memory utilized by each application, PID of each application and path to a folder where each application image is stored.
Total system shared memory	Indicates the total amount of system memory that can be utilized by this GPU adapter.	MB	Shared memory represents system memory that can be used by the GPU. Shared memory can be used by the CPU for processing normal system tasks needed or as “video memory” for the GPU while processing video tasks.
Used system shared memory	Indicates the amount of system memory that is utilized by this GPU adapter.	MB	Ideally, a low value is desired for this measure.
Free system shared memory	Indicates the amount of system memory that is available for use by this GPU adapter.	MB	The value of this measure should be high.
System shared usage	Indicates the percentage of system memory that is utilized by this GPU adapter.	Percent	Use the detailed diagnosis of the this measure to find out the names of top-10 applications that are over-utilizing the system shared memory. Administrators can also find out the percentage of dedicated memory utilized by each application, PID of each application and path to a folder where each application image is stored.
System video memory	Indicates the amount of system video memory that can be used by this GPU adapter.	MB
Total committed memory	Indicates the total amount of committed memory allocated for this GPU adapter.	MB	Use the detailed diagnosis of the Total committed memory measure to find out the names of top-10 applications that are over-utilizing the GPU committed memory. Administrators can also find out the percentage of dedicated memory utilized by each application, PID of each application and path to a folder where each application image is stored.
GPU utilization	Indicates the percentage of this GPU adapter utilized in this VM.	Percent	A value close to 100% is a cause of concern which requires further investigation. Compare the value of this measure across the GPU adapters to know the GPU adapter that is being over-utilized. The detailed diagnosis of this measure lists the names of top-10 applications in descending order based on the percentage of overall GPU utilization. Administrators can also find out the PID of application and path to a folder where the application image is stored.
3D utilization	Indicates the percentage of this GPU adapter utilized for processing 3D frames.	Percent	Compare the value of this measure across the GPU adapters to identify the GPU adapter that is being over-utilized. The detailed diagnosis of this measure lists the names of top-10 applications in descending order based on the percentage of GPU utilized for processing 3D frames. Administrators can also find out the PID of application and path to a folder where the application image is stored.
Video decode utilization	Indicates the percentage of this GPU adapter utilized for performing video decoding process.	Percent	The detailed diagnosis of this measure lists the names of top-10 applications in descending order based on the percentage of GPU utilized for video decoding process. Administrators can also find out the PID of application and path to a folder where the application image is stored.
Copy utilization	Indicates the percentage of this GPU adapter utilized for copying operations.	Percent	The detailed diagnosis of this measure lists the names of top-10 applications in descending order based on the percentage of GPU utilized for copying operations. Administrators can also find out the PID of application and path to a folder where the application image is stored.
Video processing utilization	Indicates the percentage of this GPU adapter utilized for processing video frames.	Percent	Compare the value of this measure across the GPU adapters to figure out which GPU adapter is over-utilized for processing video frames.