Balance is the key to an efficient system. Too little storage may not give you the space for critical applications. And too much power can cause you to waste money on energy you don’t need. The same goes for processors, RAM, network adapters, etc. When you don’t align your hardware with your needs, you’re going to run into performance issues. Virtualization is no different. Whether virtualized or running on bare metal hardware, applications have similar needs. For example, software that powers gaming, simulation, and video and photo editing are all processor intensive. Running these types of applications solely on CPUs will give you poor performance at best. Using GPU virtualization can make your machines much more efficient. For example, when  GPU virtualization is used for specific applications, it can cut CPU usage by two-thirds. What is GPU virtualization? It’s when you take physical GPUs and use them to render graphics for your virtual machines – similar to virtualizing other components like storage and CPUs. Let’s take a look at how GPU virtualization is being used today.

Enhance User Experience With GPU Virtualization

User experience is a key indicator of how well your IT infrastructure is working. When applications are sluggish, or you experience bottlenecks due to unoptimized systems, it means you need to adjust your computing resources. One such adjustment is to balance workloads using vGPU resources. Here are three use cases for GPU virtualization:
  1. Boost the performance of virtual machines. Non-GPU virtual machines are limited in parallel processing due to the insufficient number of cores in CPUs. In contrast, GPUs have thousands of cores that speed up tasks in AI, ML, gaming, and other compute-intensive use cases.
  2. Reduce system bottlenecks. One of the uses of virtualization in business is to make computing resources and data available to users. A system that only uses CPUs will get bogged down during peak workloads. Using GPUs and CPUs together allows virtual machines to distribute workloads better and maintain strong performance.
  3. Enable applications that rely on GPU capabilities. Cloud gaming, AI software, and desktop virtualization are all applications that depend on GPU hardware to run smoothly. In gaming, lag makes or breaks the user experience. And with AI, slow computation can be the difference between running ML models in hours or days. Speeding up these tasks makes working in the cloud viable.
The applications of GPU virtualization continue to expand as the underlying hardware becomes more powerful. Today, virtualized hardware runs almost as efficiently as its physical counterparts.

Leverage GPU Virtualization in Your Business

Organizations are always looking for ways to use their resources better. Virtualization allows businesses to improve infrastructure utilization management, increasing the ROI of their equipment. For example, GPUs tend to be costly. Virtualizing them means they are not sitting dormant and unusable when a machine isn’t running. Building computing infrastructure that supports edge and cloud computing is not as easy as adding something to your Amazon cart. Instead, companies need to consider compatibility with current systems, sourcing, and deployment. Intequus offers full-lifecycle hardware support that takes care of everything from design to decommissioning. If you’re considering GPU virtualization, chat with one of our specialists about your options.

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