Why NVIDIA GRID™ vGPU™ for desktop virtualization?

Introduction

‘What is VDI?’

It comes as no surprise that this is a common question in the IT world. It is all the more so in non-technical forums where most continue to learn the concept of VDI.

Let’s start with a simple Virtual Desktop Infrastructure VDI definition. This technology isolates users’ applications from PCs and allows them to access the VM from client devices across a network. You can use your virtual desktop in the same way as you would interact with a physical desktop. The added benefit is you can gain remote access to your virtual desktop and applications anytime, anywhere and on any device.

Why Use GPU for VDI?

Today, you can choose from many platforms to improve IT infrastructure ability. There is a greater need for engaging and affordable solutions that deliver exceptional user experience. VDI turns this into reality by assigning a dedicated GPU to each virtual machine to boost performance and end UX.

Here’s the tricky side. Finding the perfect solution that can meet different IT needs remains one of the greatest challenges to this day. Also, you must facilitate access to high-performance virtualization applications for maximum performance at all times. This is important especially if you have a large number of users and IT resources in your workplace.

Keeping this in view, let’s look at what vGPU technology can do for your virtual desktop environment.

The following is a brief guide to selecting the ideal GPU for your needs. After this, we shall look at how NVIDIA vGPU GRID complements VDI.

Choosing the Best GPU for Virtualization

Most GPUs offer scalability and complete application availability. Even then, the real challenge is to provide smooth and interactive UX in broad use cases. Ideally, you should go for a solution based on user GPU demands in VDI setups.

Why so? The reason is users who run basic applications do not have professional graphics design related duties. This group does not need hardware accelerated graphics or a dedicated graphics card for extensive uses. An example is Big Data visualization which involves high resolution and frame rates. On the other hand, other users perform advanced IT functions and have a deeper understanding of complex tasks and processes.

Considering their skill levels, divide the system requirements of these users into standard, mid-range and high-end groups.

Users who run professional 3D applications need heavy duty graphics cards to push visual quality to the next level. Examples are designers who often build, edit and render large 3D models while engineers follow up by editing these prototypes. They demand enterprise class graphic accelerators and resources that can withstand their workloads.

Mid-level users generally perform on a smaller scale than power users. Even then, this group may run applications where they draw up comprehensive 3D models for to perform related tasks.

So, carrying out workload analysis is a must for GPU-based scalability and a good optimization strategy.

How does vGPU GRID work?

NVIDIA developed GRID software to boost mobility, security and productivity. This is done by virtualizing and allocating GPUs across a large number of VMs and applications. NVIDIA vGPU drives the highest possible standards of elasticity, security and transparency in all virtual workloads. How does this work? The GRID-enabled hypervisor and vGPU solution is set up at the virtualization layer. vGPU software then creates vGPUs so that the physical GPU installed on the server is allocated between all VMs.

The virtualization software comes with an independent graphics driver for every VM. This allows the CPU to offload workloads to the GPU which supports graphics-intensive applications.

Now, let’s look at why you should adopt vGPU GRID for VDI.

Rich End User Experience (UX)

Successful VDI planning begins with you recognizing and understanding diverse user needs in the workplace. As discussed, NVIDIA virtual GPU software optimizes desktop, application and workstation virtualization by distributing vGPUs to users across the office. It also supports a wide range of heavy lifting multimedia, creative and engineering applications in different VDI setups.

Team members have changed the way they perform in these VDI settings. As a result, modern graphics-intensive applications and OS must be immersive, consistent and productive. This is all the more important for remote users who demand access to specialized applications. With a GRID-based virtualized platform, users can access and work with rich visual content anywhere and anytime.

NVIDIA vGPU also facilitates high density and general purpose IT setups through server-side graphics, monitoring and administrative efficiencies. This enables a VDI environment to stand out with quality graphics in AI, creative, designing and engineering (CAE/CAM/CAD) forums. All these lead to the highest possible levels of UX.

Powerful Management and Monitoring Competencies

IT teams oversee virtual workflow processes where users often perform multiple tasks at the same time. Two common examples include image and video rendering.

NVIDIA vGPU in VDI allows you to ensure proactive end-to-end monitoring. This produces actionable user and application insights that help achieve workspace visibility and transparency. Companies can also reveal excessive usage patterns by isolating GPU bottlenecks that may affect productivity and overall UX.

Monitoring vGPU usage on VMs in real-time boosts responsiveness to workflows and GPU performance especially during crunch time. Also, use NVIDIA vGPU to identify potential lags in VMs before they cause any real damage. This promotes fast issue resolution and smart resource planning to streamline workplace activities.

Integrate the vGPU software into an open NVIDIA SDK to create customized IT system monitoring and management settings. This makes use of host, guest and application analytics to promote data-driven decision making and improve UX. In this way, it also becomes easier for users to meet expected performance levels. All in all, you get to maximize productivity in enterprise-level VDI setups.

Flexible Administration and Scaling

GRID vGPU goes beyond playing an important role in virtualizing graphics. It also drives interactive onsite and offsite experiences by securing workloads in the data center. So, monitoring GPU is important so that you are aware of the extent to which you are drawing on its capability.

A good GPU management solution is the Data Center GPU Manager (DCGM). This helps IT track GPU health and increase datacenter throughput in the accelerated datacenter. Companies can make use of vGPU and DCGM to raise productivity standards to a whole new level.

NVIDIA not only offers advanced solutions that scale across GPUs in a system. Its range also includes GPU Cloud Rendering which facilitates interactive 3D UX on smartphones, laptops and tablets. This provides easier access to users in places where VDI and BYOD programs work in tandem to deliver engaging UX.

You can also configure unique user login credentials based on their graphics demands and application workloads. For example, assign a NVIDIA GRID K2 board to 16 engineers, data scientists and researchers who carry out deep learning tasks. Task or knowledge users who perform less complex roles can access a GRID K1 board. This platform supports approximately 32 VMs. Using this model, IT can simplify the process of scaling user capacity as per their application and project demands.

Another example is an international architectural company which supervises virtual teams. This is where members interact with one another in the same way as they would in a physical office. VDI with vGPU-enabled technology secures data in a single location and customizes performance. This is done by allowing IT to personalize UX based on each user’s specific needs.

In this situation, a design engineer developing 3D graphics content will expect to receive the entire server’s GPU resources. On the other hand, knowledge users working on 2D applications would be assigned a smaller portion of the system’s resources. In any case, you must assess staff needs and scale performance on that basis. This will help IT set parameters for optimal GPU usage. It is also a good way to measure and maintain consistent productivity levels.

Live Migration

NVIDIA vGPU is the only platform that facilitates live migration of GPU-accelerated VMs. This makes it easier to distribute resources, boost performance, offer greater uptime/availability and prevent data loss. In fact, IT teams get more time to focus on business strategy as the need for troubleshooting decreases. Enabling live migration helps IT make upgrades and carry out maintenance without creating security risks or interrupting end user productivity. This feature also allows IT to better understand their IT systems down to the application level. So, you can proactively localize an issue before it surfaces and reduce the time you would actually take to solve one.

In this way, you can level out workloads to achieve optimal user density and provision resources that accurately meet their demands.

To Sum Things Up

Technology is only useful if it helps realize outcomes that guide companies to success in the long run. Keeping this in view, assume that you want to go the vGPU route to boost scalability and achieve lower TCO. With vGPU software, you can fine-tune resource allocation and decrease latency on graphics-heavy apps and Thin Clients.

In the end, it is all about getting the most value for money. You do this investing in VDI resources that meet the needs of modern graphics-intensive applications. NVIDIA GRID™ vGPU™ delivers in every sense, and key industries benefit.

Is vGPU suitable for all use cases?

vGPU effectively supports VDI once you know why and when it is worth investing in. It all comes down to your end users and the nature of work they do. For example, vGPU technology would not be the right fit for your company if your staff mostly consists of task workers. Using Raspberry Pi Thin Client for VDI will do for this group because the client side does not involve intensive processing.

At its core, NVIDIA virtual GPUs are ideal for knowledge workers. These users may find themselves running graphics-intensive software at some point in time. So, the virtual desktops and applications they access need accelerated graphics for a PC-like experience. You can bring this about by combining GRID vPC and GRID vApps. What’s more, these platforms feature support for 24 concurrent users on a physical GPU.

Next, think about which GPU technology would work best for you. Will it be integrated or dedicated? Once again, deciding between the best option needs time, research and an understanding of your business model.

A quick and easy option is to consider ClearCube CVDI solutions for your VDI setup. For example, our PCoIP Blade PCs work well in places where power users need a dedicated graphics card to perform tasks. These integrated PCoIP and GPU devices offer the fastest datacenter to desktop connections for great performance and easy manageability.

For more details on our CVDI range, please click here .

Closing Thoughts

vGPU GRID technology is just another name for rich and interactive graphics experience across VMs. In a nutshell, this solution does more than just deliver security, manageability and support across VDI setups. The technology serves as a benchmark for creating quality enterprise IT deliverables. This, in turn, allows users to follow through with actionable plans.

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