Fri Mar 04 2022
Virtual GPU (vGPU): Enhancing Graphics Performance in Virtual Environments
In the world of computing, the demand for graphics performance has grown exponentially, driven by applications ranging from video editing and 3D modeling to scientific simulations and gaming. However, achieving high-quality graphics in virtualized environments, such as virtual desktop infrastructure (VDI) or cloud-based services, can be challenging. This is where Virtual GPU (vGPU) technology comes into play. In this article, we'll explore what vGPU is and how it works to deliver enhanced graphics performance in virtual environments.
Understanding Virtual GPU (vGPU)
A Virtual Graphics Processing Unit (vGPU) is a computer processor that renders graphics on multiple virtual machine's (VM's) host server rather than on a physical endpoint device to share the processing power of a physical GPU (Graphics Processing Unit). It provides each VM with dedicated GPU resources, ensuring that applications requiring GPU acceleration can run smoothly within a virtualized environment. Virtual GPU reduces the lag time when delivering graphics to remote users and providing the same performance they would get from a PC. This is especially useful for users that require computer-aided design or 3D graphics applications.
Though Virtual Desktop Infrastructure (VDI) is a great way to deliver desktops and apps to workers. But it's not ideal for delivering the type of performance power users need to accomplish work with apps that display complex graphics. That's where Virtual Graphics Processing Unit (vGPU) cards come in. NVIDIA introduced the first virtual GPU in 2012 to help to solve that problem. This virtualized GPU power also creates changes on the company's back end. Saved CPU cycles lead to saved costs in hardware, floor space, and cooling. There are also savings on the front end by way of computer, network and cooling costs. Virtual GPU is a great technology to satisfy multiple users with a GPU. Though Intel, AMD, and Nvidia are continuously working on this technology.
Fundamental types of Virtual GPU
1. API Intercept
The oldest of these, API Intercept, works at the OpenGL and DirectX level. It intercepts commands via an API, sends them to the GPU, then gets them back and shows the results to the user. Since this is all done in software, no GPU features are exposed. This also means that the software capabilities tend to lag behind the GPU in terms of what APIs are supported. API Intercept typically has good performance when it works. It's the only method that supports vMotion.
Pass-through, which if memory serves has been around for longer than Virtualized GPU, connects virtual machines directly to a GPU. If you have two cards in your server, then you get to connect two VMs to GPUs while everyone else gets nothing. This is great for the highest-end workloads since VMs get access to all of the GPU and its features and application compatibility is great. Pass-through is the most expensive by far, and other than the high-end use case, the only other use cases are either GPGPU or as a reward for good performance at work.
3. Virtualized GPU
This is the hottest spot in desktop virtualization today, spare maybe storage and hyper-converged infrastructure. With Virtualized GPU, users get direct access to a part of the GPU. This is preferable to API Intercept because the OS uses the real AMD/NVIDIA/Intel drivers, which means applications can use native graphics calls as opposed to a genericized subset of them. It has better performance than API Intercept. Though it gives applications direct access to the CPU, the users are only getting a portion of the CPU, so it can still be limited in certain situations. That said, the application compatibility is good, but vMotion is not supported.
Features of vGPU
1. True hardware virtualization with NVIDIA vGPU
Graphics applications have direct access to the GPU, reducing system latency and improving performance with complex 3D workloads.
2. Native graphics hardware stack
Drivers support for the latest OpenGL and DirectX libraries for maximum application compatibility and performance, thanks to end-to-end graphics stack by NVIDIA (hardware, Windows driver, hypervisor manager).
3. Leverage FlexCast services
Balance high performance and optimum scalability with choice of delivering just the apps, or full desktop using the FlexCast delivery model in XenDesktop and XenApp, supporting HDX optimizations for the low-bandwidth and broad range of client devices.
4. Hypervisor Requirements and Hypervisor Support
Both Intel and NVIDIA require a software manager to be installed into the hypervisor. This isn’t a big deal since both GPUs are certified to run on certain platforms (more on that in a minute), but it is an extra step. AMD utilizes SR-IOV, which essentially means that they designed their card to present itself to the BIOS in such a way that the BIOS treats it as if it’s several cards, which means you don’t need a software component in the hypervisor itself.
How Virtual GPU (vGPU) Works
1. Hypervisor Integration
vGPU technology is tightly integrated with the hypervisor, the software layer that manages and allocates physical resources to VMs. Popular hypervisors like VMware vSphere, Citrix XenServer, and Microsoft Hyper-V offer support for vGPU.
2. Physical GPU Partitioning
The physical GPU is divided into multiple virtual GPUs, each of which is assigned to a specific VM. These virtual GPUs are sometimes referred to as vGPU profiles and can vary in terms of performance capabilities.
3. GPU Virtualization
The hypervisor and GPU driver work together to virtualize the GPU's resources. Each VM interacts with its dedicated vGPU as if it were a physical GPU, unaware that it's sharing the hardware with other VMs.
4. GPU Scheduling
To ensure fair and efficient utilization of the physical GPU, a GPU scheduler arbitrates access to the GPU resources. This scheduler manages the GPU's execution context, prioritizing and scheduling tasks from different VMs.
5. Frame Buffer Sharing
While each VM has its vGPU, they may share the GPU's frame buffer, which is where the rendered images and graphical data are stored temporarily. Frame buffer sharing allows VMs to efficiently exchange data, enhancing performance.
6. GPU Driver Support
To use vGPU technology, VMs must have the appropriate GPU drivers installed. These drivers are specially designed to work with virtualized GPUs and provide the necessary interface for VMs to communicate with the physical GPU.
Benefits of Virtual GPU (vGPU)
1. Improved Performance
vGPU technology enables VMs to access dedicated GPU resources, ensuring smooth and high-performance graphics for applications that require it.
2. Resource Efficiency
By sharing a single physical GPU among multiple VMs, vGPU maximizes GPU utilization and reduces hardware costs.
Each VM has its vGPU, ensuring isolation and preventing one VM's activities from affecting the performance or stability of others.
vGPU profiles come in various performance levels, allowing organizations to allocate GPU resources based on workload requirements.
As GPU demands grow, organizations can add more physical GPUs to their infrastructure and scale up graphics performance easily.
vGPU technology finds applications in various fields, including:
1. Virtual Desktop Infrastructure (VDI)
Enhancing the graphics performance of virtual desktops, enabling tasks like video editing and 3D modeling in VDI environments.
2. Cloud Gaming
Delivering high-quality gaming experiences to users through cloud-based gaming platforms.
3. Scientific and Engineering Simulations
Accelerating simulations used in scientific research and engineering tasks.
Virtual GPU (vGPU) technology has revolutionized the way virtualized environments handle graphics-intensive workloads. By efficiently sharing physical GPU resources among multiple VMs, vGPU ensures optimal graphics performance while reducing hardware costs and providing isolation between VMs. As the demand for GPU acceleration continues to grow in virtual environments, vGPU technology plays a pivotal role in meeting these demands effectively and efficiently.