A user running a Computer Aided Design (CAD) application is complaining about slow response time within the VM, particular when moving windows or rendering images.
Which VM metric will guide the administrator toward diagnosing the problem?
A GPU (graphics processing unit) is a specialized hardware device that can accelerate graphics rendering and computation for applications that use APIs such as DirectX, OpenGL, CUDA, and OpenCL. A GPU can also offload the CPU from encoding and decoding tasks for remote display protocols such as Frame Remote Desktop Protocol (FRP). A VM can use a GPU either by directly accessing a physical GPU (pGPU) on the host or by using a virtual GPU (vGPU) that shares a pGPU with other VMs. A user running a computer aided design (CAD) application may benefit from using a GPU or a vGPU to improve the performance and responsiveness of the application, especially when moving windows or rendering images. However, if the GPU or vGPU is not properly configured or provisioned, the user may experience slow response time within the VM. Therefore, to diagnose the problem, the administrator should monitor the GPU Usage metric for the VM. The GPU Usage metric shows the percentage of GPU resources that are consumed by the VM over time3. The administrator can use Prism Central to view the GPU Usage metric for each VM in a chart or a widget4. The administrator can also use Prism Central to view other metrics related to GPU performance, such as GPU Memory Usage, GPU Encoder Usage, and GPU Decoder Usage3. By analyzing these metrics, the administrator can determine if the VM is using the GPU efficiently and optimally, or if it needs more or less GPU resources.
[Reference: Nutanix Frame and GPU: Options, Tools, and Best Practices, ]
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