Creating clarity through multiple lenses
Thu, 20 Jul 2023 16:56:33 -0000
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Originally published on August 20, 2019
With just a single lens, a camera captures objects in 2D space. Using only the camera on a cellphone, users are capable of recording ultra-high definition video and playing back on their home entertainment screens with amazing fidelity. While the movie depicts a masterful 3D scene, we are only perceiving the realistic nature by remaining in our seats. Moving from side to side will not allow the viewer to see objects not captured by the camera. We remain satisfied with our viewing experience for media, as we are given the view that the recorder intended.
Adding another camera to a phone allows users to capture another dimension, depth. Ironically, the images from each lens look extremely similar and oftentimes are not noticeably different, unless viewed side-by-side. The minor differences exist between images but when viewed on a 3D supported television they provide an impressive experience emulating reality. While 3D television may not be the preference for all viewers of media, it does prove that adding a second lens can provide an additional measurement of depth, which is precisely the point.
Dell EMC is adding an additional perspective to our infrastructure considerations and guidelines for VDI (click here to access designs from our Info Hub). In the past, Dell and Dell EMC have relied solely on the LoginVSI scores under specific testing thresholds to provide our guidance for user density and sizing expectations. This benchmarking tool has been a positive and reliable industry standard benchmark and it will remain a part of our design guidance based on its effectiveness at displaying a maximum threshold for VDI. To complement that perspective, Dell EMC VDI Solutions will, where appropriate, begin using the NVIDIA nVector to provide the second lens necessary for focusing on experience.
The NVIDIA nVector toolset has the ability to monitor the VDI experience in different ways than LoginVSI. LoginVSI focuses mainly on server-side metrics and measures individual components throughout the load test. NVIDIA nVector does utilize server side metrics but adds client side measurements to monitor frame rate, latency, and protocol fidelity (or accuracy). These elements are more geared towards measuring how the end user perceives the experience, whereas the LoginVSI focuses on optimizing to the maximum limitations of the hardware. Since VDI solutions are comprised of components beyond the server, a holistic measurement tool for the entire VDI environment gives Dell EMC the ability to measure experience impacts of components, such as switches, SD-WAN, thin clients, and more.
Come find out more about the benefits of Dell EMC VDI Solutions at VMworld 2019, as we present in the NVIDIA booth, our executive suite (click to register for the event), as well as the many great VDI sessions from Dell Technologies. We hope you'll gain from our enhanced perspective.
Published By
David Pfahler
Solution Product Manager
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Dell EMC vSAN Ready Nodes: Taking VDI and AI Beyond “Good Enough”
Mon, 18 Oct 2021 13:06:37 -0000
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Some people have speculated that 2020 was “the year of VDI” while others say that it will never be the “year of VDI.” However, there is one certainty. In 2020 and part of 2021, organizations worldwide consumed a large amount of virtual desktop infrastructure (VDI). Some of these deployments went extremely well while other deployments were just “good enough.”
If you are a VDI enthusiast like me, there was much to learn from all that happened over the last 24 months. An interesting observation is that test VDI environments turned into production environments overnight. Also, people discovered that the capacity of clouds is not limitless. My favorite observation is the discovery by many IT professionals that GPUs can change the VDI experience from “good enough” to enjoyable, especially when coupled with an outstanding environment powered by Dell Technologies with VMware vSphere and VMware Horizon.
In this blog, I will tell you about how exceptional VDI (and AI/ML) is when paired with powerful technology.
This blog does not address cloud workloads as it is a substantial topic. It would be difficult for me to provide the proper level of attention in this blog, so I will address only on premises deployments.
Many end users adopt hyperconverged infrastructure (HCI) in their data centers because it is easy to consume. One of the most popular HCIs is Dell EMC VxRail Hyperconverged Infrastructure. You can purchase nodes to match your needs. These needs range from the traditional data center workloads, to Tanzu clusters, to VDI with GPUs, and to AI. VxRail enables you to deliver whatever your end users need. Your end users might be developers working from home on a containers-based AI project and they need a development environment, VxRail can provide it with relative ease.
Some IT teams might want an HCI experience that is more customer managed but they still want a system that is straightforward to deploy, validate, and is easy to maintain. This scenario is where Dell EMC vSAN Ready Nodes come into play.
Dell EMC vSAN Ready Nodes provide comprehensive, flexible, and efficient solutions optimized for your workforce’s business goals with a large choice of options (more than 250 as of the September 29, 2021 vSAN Compatibility Guide) from tower to rack mount to blades. A surprising option is that you can purchase Dell EMC vSAN Ready Nodes with GPUs, making them a great platform for VDI and virtualized AI/ML workloads.
Dell EMC vSAN Ready Nodes supports many NVIDIA GPUs used for VDI and AI workloads, notably the NVIDIA M10 and A40 GPUs for VDI workloads and the NVIDIA A30 and A100 GPUs for AI workloads. There are other available GPUs depending on workload requirements, however, this blog focuses on the more common use cases.
For some time, the NVIDIA M10 GPU has been the GPU of choice for VDI-based knowledge workers who typically use applications such as Microsoft PowerPoint and YouTube. The M10 GPU provides a high density of users per card and can support multiple virtual GPU (vGPU) profiles per card. The multiple profiles result from having four GPU chips per PCI board. Each chip can run a unique vGPU profile, which means that you can have four vGPU profiles. That is, there are twice as many profiles than are provided by other NVIDIA GPUs. This scenario is well suited for organizations with a larger set of desktop profiles.
Combining this profile capacity with Dell EMC vSAN Ready Nodes, organizations can deliver various desktop options yet be based on a standardized platform. Organizations can let end users choose the system that suites them best and can optimize IT resources by aligning them to an end user’s needs.
Typically, power users need or want more graphics capabilities than knowledge workers. For example, power users working in CAD applications need larger vGPU profiles and other capabilities like NVIDIA’s Ray Tracing technology to render drawings. These power users’ VDI instances tend to be more suited to the NVIDIA A40 GPU and associated vGPU profiles. It allows power users who do more than create Microsoft PowerPoint presentations and watch YouTube videos to have the desktop experience they need to work effectively.
The ideal Dell EMC vSAN Ready Nodes platform for the A40 GPU is based on the Dell EMC PowerEdge R750 server. The PowerEdge R750 server provides the power and capacity for demanding workloads like healthcare imaging and natural resource exploration. These workloads also tend to take full advantage of other features built into NVIDIA GPUs like CUDA. CUDA is a parallel computing platform and programming model that uses GPUs. It is used in many high-end applications. Typically, CUDA is not used with traditional graphics workloads.
In this scenario, we start to see the blend between graphics and AI/ML workloads. Some VDI users not only render complex graphics sets, but also use the GPU for other computational outcomes, much like AI and ML do.
I really like that I can run AI/ML workloads in a virtual environment. It does not matter if you are an IT administrator or an AI/ML administrator. You can run AI and ML workloads in a virtual environment.
Many organizations have realized that the same benefits virtualization has brought to IT can also be realized in the AI/ML space. There are additional advantages, but those are best kept for another time.
For some organizations, IT is now responsible for AI/ML environments, whether delivering test/dev environments for programmers or delivering a complete AI training environment. For other IT groups, this responsibility falls to highly paid data scientists. And for some IT groups, the responsibility is a mix.
In this scenario, virtualization shines. IT administrators can do what they do best: deliver a powerful Dell EMC vSAN Ready Node infrastructure. Then, data scientists can spend their time building systems in a virtual environment consuming IT resources instead of racking and cabling a server.
Dell EMC vSAN Ready nodes are great for many AI/ML applications. They are easy to consume as a single unit of infrastructure. Both the NVIDIA A30 GPU and the A100 GPU are available so that organizations can quickly and easily assemble the ideal architecture for AI/ML workloads.
This ease of consumption is important for both IT and data scientists. It is unacceptable when IT consumers like data scientists must wait for the infrastructure they need to do their job. Time is money. Data scientists need environments quickly, which Dell EMC vSAN Ready Nodes can help provide. Dell EMC vSAN Ready Nodes deploy 130 percent faster with Dell EMC OpenManage Integration for VMware vCenter (OMIVV) (Based on Dell EMC internal competitive testing of PowerEdge and OMIVV compared to Cisco UCS manual operating system deployment.)
This speed extends beyond day 0 (deployment) to day 1+ operations. When using the vLCM and OMIVV, complete hypervisor and firmware updates to an eight-node PowerEdge cluster took under four minutes compared to a manual process, which took3.5 hours.(Principle Technologies report commissioned by Dell Technologies, New VMware vSphere 7.0 features reduced the time and complexity of routine update and hardware compliance tasks, July 2020.)
Dell EMC vSAN Ready Nodes ensures that you do not have to be an expert in hardware compatibility. With over 250 Dell EMC vSAN Ready Nodes available (as of the September 29, 2021 vSAN Compatibility Guide), you do not need to guess which drives will work or if a network adapter is compatible. You can then focus more on data and the results and less on building infrastructure.
These time-to-value considerations, especially for AI/ML workloads, are important. Being able to deliver workloads such as AI/ML or VDI quickly can have a significant impact on organizations, as has been evident in many organizations over the last two years. It has been amazing to see how fast organizations have adopted or expanded their VDI environments to accommodate everyone from knowledge workers to high-end power users wherever they need to consume IT resources.
Beyond “just expanding VDI” to more users, organizations have discovered that GPUs can improve the end-user experience and, in some cases, not only help but were required. For many, the NVIDIA M10 GPU helped users gain the wanted remote experience and move beyond “good enough.” For others who needed a more graphics-rich experience, the NVIDIA A40 GPU continues to be an ideal choice.
When GPUs are brought together as part of a Dell EMC vSAN Ready Node, organizations have the opportunity to deliver an expanded VDI and AI/ML experience to their users. To find out more about Dell EMC vSAN Ready Nodes, see Dell EMC vSAN Ready Nodes.
Author: Tony Foster Twitter: @wonder_nerd LinkedIn: https://linkedin.com/in/wondernerd
Breaking down the barriers for VDI with VxRail and NVIDIA vGPU
Wed, 21 Apr 2021 15:17:54 -0000
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Desktop transformation initiatives often lead customers to look at desktop and application virtualization. According to Gartner, “Although few organizations planned for the global circumstances of COVID-19, many will now decide to have some desktop virtualization presence to expedite business resumption.”
However, customers looking to embrace these technologies have faced several hurdles, including:
- Significant up-front CapEx investments for storage, compute, and network infrastructure
- Long planning, design, and procurement cycles
- High cost of adding additional capacity to meet demand
- Difficulty delivering a consistent user experience across locations and devices
These hurdles have often caused desktop transformation initiatives to fail fast, but there is good news on the horizon. Dell Technologies and VMware have come together to provide customers with a superior solution stack that will allow them to get started more quickly than ever, with simple and cost-effective end-to-end desktop and application virtualization solutions using NVIDIA vGPU and powered by VxRail.
Dell Technologies VDI solutions powered by VxRail
Dell Technologies VDI solutions based on VxRail feature a superior solution stack at an exceptional total cost of ownership (TCO). The solutions are built on Dell EMC VxRail and they leverage VMware Horizon 8 or Horizon Apps and NVIDIA GPU for those who need high-performance graphics. Wyse Thin and Zero client, OptiPlex micro form factor desktop, and Dell monitors are also available as part of these solutions. Simply plug in, power up, and provision virtual desktops in less than an hour, reducing the time needed to plan, design, and scale your virtual desktop and application environment.
VxRail HCI system software provides out-of-the-box automation and orchestration for deployment and day-to-day system-based operational tasks, reducing the overall IT OpEx required to manage the stack. You are not likely to find any build-it-yourself solution that provides this level of lifecycle management, automation, and operational simplicity
Dell EMC VxRail and NVIDIA GPU a powerful combination
Remote work has become the new normal, and organizations must enable their workforces to be productive anywhere while ensuring critical data remains secure.
Enterprises are turning to GPU-accelerated virtual desktop infrastructure (VDI) because GPU-enabled VDI provides workstation-like performance, allowing creative and technical professionals to collaborate on large models and access the most intensive 3D graphics applications.
Together with VMware Horizon, NVIDIA virtual GPU solutions help businesses to securely centralize all applications and data while providing users with an experience equivalent to the traditional desktop.
NVIDIA vGPU software included with the latest VMware Horizon release, which is available now, helps transform workflows so users can access data outside the confines of traditional desktops, workstations, and offices. Enterprises can seamlessly collaborate in real time, from any location, and on any device.
With NVIDIA vGPU and VMware Horizon, professional artists, designers, and engineers can access new features such as 10bit HDR and high-resolution 8K display support while working from home by accessing their virtual workstation.
How NVIDIA GPU and Dell EMC VxRail power VDI
In a VDI environment powered by NVIDIA virtual GPU, the virtual GPU software is installed at the virtualization layer. The NVIDIA software creates virtual GPUs that enable every virtual machine to share a physical GPU installed on the server or allows for multiple GPUs to be allocated on a single VM to power the most demanding workloads. The NVIDIA virtualization software includes a driver for every VM. Because work that was previously done by the CPU is offloaded to the GPU, the users, even demanding engineering and creative users, have a much better experience.
Virtual GPU for every workload on Dell EMC VxRail
As more knowledge workers are added on a server, the server will run out of CPU resources. Adding an NVIDIA GPU offloads CPU operations that would otherwise use the CPU, resulting in an improved user experience and performance. We used the NVIDIA nVector knowledge worker VDI workload to test user experience and performance with NVIDIA GPU. The NVIDIA M10, T4, A40, RTX6000/8000 and V100S, all of which are available on Dell EMC VxRail, achieve similar performance for this workload.
Customers are realizing the benefits of increased resource utilization by leveraging GPU-accelerated Dell EMC VxRail to run virtual desktops and workstations. They are also leveraging these resources to run compute workloads, for example AI or ML, when users are logged off. Customers who want to be able to run compute workloads on the same infrastructure on which they run VDI, might leverage a V100S to do so. For the complete list, see NVIDIA GPU cards supported on Dell EMC VxRail.
Conclusion
With the prevalence of graphics-intensive applications and the deployment of Windows 10 across the enterprise, adding graphics acceleration to VDI powered by NVIDIA virtual GPU technology is critical to preserving the user experience. Moreover, adding NVIDIA GRID with NVIDIA GPU to VDI deployments increases user density on each server, which means that more users can be supported with a better experience.
To learn more about measuring user experience in your own environments, contact your Dell Account Executive.
Useful links
Video: VMware Horizon on Dell Technologies Cloud
Dell Technologies Solutions: Empowering your remote workforce
Certified GPU for VxRail: NVIDIA vGPU for VxRail[
Everything VxRail: Dell EMC VxRail
VDI Design Guide: VMware Horizon on VxRail and vSAN Ready Nodes
Latest VxRail release: Simpler cloud operations and more deployment options!