{"id":4217,"date":"2016-02-16T12:00:03","date_gmt":"2016-02-16T17:00:03","guid":{"rendered":"https:\/\/www.eginnovations.com\/blog\/?p=4217"},"modified":"2025-05-15T03:24:14","modified_gmt":"2025-05-15T07:24:14","slug":"citrix-gpu-monitoring","status":"publish","type":"post","link":"https:\/\/www.eginnovations.com\/blog\/citrix-gpu-monitoring\/","title":{"rendered":"GPU Monitoring for Digital Workspaces"},"content":{"rendered":"

<\/span>What is a GPU?<\/span><\/h2>\n

\"eG<\/a>A Graphical Processing Unit (GPU) is a specialized integrated chip designed to handle graphics processing for applications like 3-D gaming, scientific, analytics, engineering, consumer, and industrial applications like CAD. When a GPU is present, it handles the graphics processing, leaving computational processing to the traditional CPU. Architecturally, while a CPU has only few cores and handles a few hundred threads at a time, a GPU is composed of hundreds of cores that can handle thousands of threads simultaneously and render a flawless, rich graphics experience.<\/p>\n

With recent advances in GPU technology, it is now possible to virtualize GPUs. With a virtual GPU (vGPU), graphics can be rendered on a virtual machine\u2019s (VM\u2019s) host server rather than on a physical end-point device. This technology makes it possible to use virtual desktop technology to support users accessing graphics-intensive workloads. Leading hypervisors, including VMware vSphere and Citrix XenServer, support virtual GPU technologies now. GPU sharing across users is also supported for application virtualization technologies like Citrix XenApp and Microsoft remote desktop services.<\/p>\n

Explore GPU Monitoring Capabilities \u00bb<\/a><\/div>\n

<\/span>Why GPU Technology is Important for Digital Workspaces?<\/span><\/h2>\n

GPU virtualization is a very important\u00a0aspect\u00a0of\u00a0successful\u00a0VDI deployment today, as\u00a0Brian Madden remarked<\/a>:<\/p>\n

\"\"<\/a>Look at regular desktops and laptops. How many of them can you buy without a GPU? And if you price out a business desktop and then you have to shave off some costs, do you ever do that by removing the GPU? No! You dial back the CPU, cut down on memory, or maybe don\u2019t do SSD. So by that logic a GPU should be 100% required for VDI, and if you don\u2019t like the \u201cadded\u201d cost of it, then you can offset it by putting 10% more users per server.<\/em><\/p><\/blockquote>\n

There are two modes of making GPU resources available to virtual desktops:<\/p>\n

A) Pass-through mode<\/strong>: In this deployment mode, a physical GPU is presented entirely to a VM (either a virtual desktop or a virtual server). In this case, there is a 1-1 mapping between the VM and GPUs. In this case, the GPU is controlled directly by the VM operating system, not the hypervisor. This mode is ideal for applications and users who require dedicated GPU resources.<\/p>\n

B) Virtual GPU (vGPU) mode: <\/strong>This model offers the benefit of sharing a physical GPU among many VMs. If a VM requires GPU resources and none of the other VMs needs GPU at the same time, it can access\u00a0all the resources of the physical GPU. vGPU technology was first introduced by NVIDIA, and the NVIDIA Grid vGPU Manager running in a hypervisor manages the GPU allocation to VMs, guaranteeing each VM has a dedicated amount of video RAM. GPU cores are time-sliced, similar to how CPU cores are time-sliced.<\/p>\n

\"eG-Enterprise-GPU-monitoring-modes\"<\/a><\/p>\n

Figure 1: Two modes of GPU allocation to VMs.<\/div>\n

<\/span>GPU Monitoring as Part of Digital Workspace Monitoring<\/span><\/h2>\n

Traditionally, performance monitoring solutions for application and desktop virtualization have tracked the utilization of CPU resources only. When GPU technology is in use, it is essential for a performance monitoring solution<\/a> to be GPU-aware. That is, the utilization of GPU resources must be tracked in the same way as the utilization of CPU. This allows\u00a0the monitoring solution to detect instances where GPU resources are a performance bottleneck, when GPU technology is not working as expected (e.g., hardware errors) and to\u00a0enable\u00a0future resource planning.<\/p>\n

For total visibility into GPU performance, it is essential to monitor:<\/p>\n