GPU Virtualization Market Trends, Key Country, Competitive Landscape and Comparative Analysis by 2025
A graphics processing unit (GPU) is a hardware that is designed to modify memory in order to accelerate the creation of image. The primary purpose of GPU is to facilitate real-time 2D/3D graphics, videos, or visual computing. GPU helps in smooth functioning of heavy videos and graphics. GPU chips nowadays often come as an embedded hardware in a computer; however, it can also be purchased independently. Primarily, the GPU is used by graphic designers; however, gaming enthusiasts or designer hobbyists also use these chips to enhance the video and image quality
A typical graphics processing unit (GPU) has storage limit and is often expensive. An efficient GPU mostly comes in the price range of USD 500-750 which is rather expensive for a mid-size company or even for an individual. Moreover, since the GPU has a storage limit, not more than one individual can efficiently use it for commercial purpose. Often, companies have to invest huge sums in this hardware. Apart from costs, there are other challenges that an organization or an individual has to face with a GPU. Such challenges include larger space requirement and requirement of powerful energy supplies. These shortcomings led to the virtualization of the graphics processing unit. The use of virtual GPU is expected to efficiently address the abovementioned challenges.
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GPU Virtualization Market – Trends and Opportunities
A virtual graphics processing unit (GPU) extracts graphics on a virtual machine’s (VMs) host server rather than on a physical end-point device. A virtual GPU allows an individual to share the GPUs present in a computer system among the other applications being executed in a cluster. Therefore with a virtualized framework, numerous applications being executed in different or the same cluster node can share one or more GPUs located in other node of the cluster. Therefore, the deployment of virtual GPU is expected to reduce the total number of GPUs installed in a cluster. In addition to the significant increase in overall GPU utilization, the virtualization of GPU is also expected to dramatically reduce the total energy consumption at a premise. When an application, a power point for instance, runs without a GPU, it consumes approximately10-12% of the CPU energy and it can even go up to 30% occasionally. However with the deployment of virtual GPU, the average energy consumption is restricted to not more than 5%.
Apps and technologies that will benefit from virtual GPU are the graphic intensive applications such as Photoshop and CAD. Additionally, other applications such as Microsoft Office, web browsers, as well as modern and advance operating systems will also obtain benefits from virtual GPU.
Some of the most common industry verticals where virtualization of GPU will prove to be beneficial are education and automotive. In the education sector, students learn CAD for which GPUs are required With virtualized GPUs universities, colleges, or even schools students as well as management will be able to optimize the use of GPU. Apart from the education sector, the automotive industry is also expected to gain significantly from virtual GPU. Engineers working in the automotive industry will gain from virtualization since they no more have to ship the physical setup around the world. Other prominent industries that are expected to use a virtual GPU set up include hospitals and clinics. Apart from specific industries, an individual can also gain benefits from a virtual GPU framework. Anyone who uses web-browser, Skype (where GPUs are required) can deploy virtual GPU in order to enhance the server density and overall experience.
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The GPU virtualization market is expected to be driven by growing need across industries for a framework that optimizes the use of GPU. Moreover, as and when more companies enter the market with their offerings, the overall GPU virtualization market is bound to accelerate.
The GPU virtualization market can be segmented as end-use application. On the basis of end-use application, the GPU virtualization market can be categorized into automotive, healthcare, education, media and entertainment and others