Introduction
The time is now for Virtual Desktop Infrastructure (VDI) using Virtual GPUs (vGPU) to take hold. Workers and devices are scattered, and employees often need to work remotely. This poses all sorts of challenges in terms of security, productivity, user adaptation, and IT management. Also, there is a shift to a greater need for engineers and designers to use 3D applications and other graphics accelerated applications with large amounts of data. In the past, CPU-only VDI environments were deployed to centralize management; however, these solutions could only reach office workers who did not need graphics acceleration, and power users, designers, and more were left out and had to stick with dedicated machines. Now, VDI has reached the point that all users who need graphics acceleration have a solution by combining VDI with vGPU. GIGABYTE has many servers specifically designed for VDI usage for productivity applications, 3D modeling, HPC applications, AI, and more.
Who needs VDI with Virtual GPUs?
Virtual Workforce
Workforce is shifting, and workers are more commonly needed to do work outside of the office. They also may have to use multiple devices, including tablets or personal phones. VDI allows users to access files remotely, while IT can securely manage the security and privacy concerns.
AI and Deep Learning
Artificial Intelligence and Deep Learning rely on the power of GPUs because most algorithms are parallelizable, which GPUs excel at, and GPUs have incredible memory bandwidth that can handle a lot of data.
Engineering & Sciences
To optimize and test designs in aerodynamics, as well as thermal simulations, these situations require the acceleration that only a GPU can offer. Engineers need access to data or high computing, and with Virtual GPUs the work is possible at a terminal separate from where the data or hardware is based.
Challenges to VDI
Several industries have been quick to adopt VDI, such as Healthcare as they needed greater compliance with regulations, and remote access became a must. However, as companies are pondering the possibility of switching there servers to VDI there are some major challenges ahead.
When we say companies need to adopt new practices we are focusing on the individuals. The switch from a personal device that is always yours to one that is simply logged in can make many users become perturbed. Add this to the fact that not all applications can be virtualized and you have a user that does not want to adopt a new way of using the PC. Convincing and showing employees that in the long term it is worth it must be done. As well, costs upfront are high for VDI architecture. Instead of buying a laptop when a user needs one, all the hardware and setup for VDI must be done before deployment of virtual devices. Last, to deploy virtual devices, IT administrators need to be onboard with the project and require high proficiency in working with servers and may need training. If these challenges can be met companies can reap the benefits of VDI.
Benefits of VDI
User Experience
Resources can better be tailored to user. As well, PC upgrades and repair takes minutes instead of hours.
Productivity & Flexibility
A dedicated, virtualized machine allows users to easily access their work-related resources from anywhere and on any device with internet.
Ease of Management
One central server location to upgrade hardware or software, as well as monitoring and patching, makes IT admins job easier.
Efficiency of Resources
Resources are not underutilized or overprovisioned. Virtual machines have optimal allocation of hardware to fit user.
VDI Architecture Explained
The concept of VDI is to use hardware in a server and allocate it to virtual machines (VM). The image on the right visualizes the allocation of resources. And the image below depicts virtualization architecture that is discussed next.
To start, a server is built with typical hardware (CPU, RAM, storage, GPU, network interconnects, etc.) that has been determined for the end users. After hardware installation, a hypervisor (Microsoft Hyper-V, Citrix XenServer, etc.) is installed to abstract the hardware. This hypervisor creates a virtualization layer upon which the VMs are built. The hypervisor that is between the VMs and the hardware contains a Virtual Machine Manager. Through this technology each VM is added with their own operating system and applications. At this point a server has virtualized all but the GPU.
To start, a server is built with typical hardware (CPU, RAM, storage, GPU, network interconnects, etc.) that has been determined for the end users. After hardware installation, a hypervisor (Microsoft Hyper-V, Citrix XenServer, etc.) is installed to abstract the hardware. This hypervisor creates a virtualization layer upon which the VMs are built. The hypervisor that is between the VMs and the hardware contains a Virtual Machine Manager. Through this technology each VM is added with their own operating system and applications. At this point a server has virtualized all but the GPU.
To create a virtual GPU, software such as NVIDIA Virtual GPU Manager installs in the hypervisor. This software coupled with other NVIDIA software (vCS, vDWS, GRID vPC, or GRID vApps) allows customization of the virtual machine. On this vGPU layer are the VMs as before, but now with NVIDIA drivers and binaries/libraries.
Virtual Machines from a Single Server
Virtualization with and without a Virtual GPU
Determine the GIGABYTE server and NVIDIA Solution
Details below are meant to help one decide on what solution fits best.
・Understand the types of users to select the appropriate NVIDIA Virtual software
・Learn about the different types of NVIDIA GPUs based on specifications and usage
・Choose from the list of GIGABYTE servers that are NVIDIA vGPU certified
・Understand the types of users to select the appropriate NVIDIA Virtual software
・Learn about the different types of NVIDIA GPUs based on specifications and usage
・Choose from the list of GIGABYTE servers that are NVIDIA vGPU certified
Types of VDI Users
Task Worker:
Basic tasks and do not need graphics acceleration.
NVIDIA Virtual Software: GRID vApps
NVIDIA GPU Used: Turing T4
Knowledge Worker:
Entry-level graphics.
NVIDIA Virtual Software: GRID vPC or Quadro vDWS
NVIDIA GPU Used: Turing T4
Power User:
Mid-level graphics to high.
NVIDIA Virtual Software: Quadro vDWS or vCS
NVIDIA GPU Used: Quadro RTX6000 or Turing T4
Designer, Engineer, AI Scientist:
High-end computing.
NVIDIA Virtual Software: vCS
NVIDIA GPU Used: Ampere A100, Quadro RTX8000, or Turing T4
Programs Used by Worker Type
| NVIDIA Accelerators for Virtualized Environment | ||||||
|---|---|---|---|---|---|---|
| A100 PCIe | RTX A6000 | A40 | Quadro RTX 8000 | Quadro RTX 6000 | T4 | |
 |
 |
 |
 |
 |
 |
|
| Architecture | Ampere | Ampere | Ampere | Turing | Turing | Turing |
| CUDA cores | 6,912 | 10,752 | 10,752 | 4,608 | 4,608 | 2,560 |
| Single-Precision | 19.5 TFLOPS | TBD | TBD | 16.3 TFLOPS | 16.3 TFLOPS | 8.1 TFLOPS |
| GPU Memory | 40 GB HBM2 | 48 GB GDDR6 | 48 GB GDDR6 | 48 GB GDDR6 | 24 GB GDDR6 | 16 GB GDDR6 |
| Memory Bandwidth | 1.6 TB/s | 768 GB/s | 696 GB/s | 672 GB/s | 624 GB/s | 320 GB/s |
| Interface | PCIe Gen 4 | PCIe Gen 4 | PCIe Gen 4 | PCIe Gen 3 | PCIe Gen 3 | PCIe Gen 3 |
| Max Power | 250W | 300W | 300W | 295W | 295W | 70W |
| Form Factor | dual-slot | dual-slot | dual-slot | dual-slot | dual-slot | single-slot |
| Usage | Ultra-high-end rendering, 3D design, AI and data science | High-end rendering, 3D design, AI, and compute workloads | Mid-range to high-end 3D design and creative workflows | High-end rendering, 3D design, and creative workflows | Mid-range to high-end rendering, 3D design and engineering, AI and data science | Entry-level to high-end 3D design and engineering, AI and data science |
| GIGABYTE Servers (NVIDIA vGPU Certified) | ||||
|---|---|---|---|---|
| NVIDIA Models | A100 PCIe | Quadro RTX 8000 | Quadro RTX 6000 | T4 |
| 1U G-series | G191-H44 | G191-H44 | G191-H44 | G191-H44 |
| 1U OCP-series | - | - | - | T181-G23, T181-G23-G24, T181-Z70 |
| 2U G-series | G291-280, G291-281, G292-Z20, G291-Z40 | G291-280, G291-281, G242-Z10, G292-Z42 | G291-280, G291-281, G242-Z10, G292-Z42 | G291-280, G291-281, G221-Z30, G242-Z10, G291-Z20, G292-Z42 |
| 2U R-series | R281-3C2, R281-G30, R282-Z93 | R282-Z93 | - | R281-G30, R281-3C2, R282-Z93 |
| 2U H-series | - | - | - | H231-G20 |
| 4U G-series | G481-HA0, G482-Z50, G492-Z50, G492-Z51 | G481-H80, G481HA0 | G481-H80, G481-HA0, G481-HA1, G482-Z50, G481-51 | G481-H80, G481-HA0, G481-HA1, G482-Z51 |
Products
1/2
2U GPU Server for Scale-out
Ideal for scale-out deployment in virtualization for GPU-centric workloads. High core count AMD EYPC™ processor and up to 4 GPUs with direct PCIe Gen4 x 16 connection to CPU. Also, 4 x 3.5" SATA and 2 x 2.5" U.2 (Gen 4)
2/2
1U GPU Server for Small Form Factor
Ideal to scale up for 5G network infrastructure or deployment in a small space. Dual Intel Xeon Scalable processors and up to 4 full-length full-height GPUs.
Related Technologies
雲端運算是什麼？
簡單地說，雲端運算(Cloud Computing)就是通過互聯網（雲）向使用者或組織（伺服器、儲存、資料庫、網路、軟體、分析、人工智慧等）提供運算資源。雲端運算通常基於虛擬化技術快速部署資源或獲得服務。雲端運算服務可以通過公有雲、私有雲或混合雲提供幾種不同的方式運作。公有雲運算由擁有實體資料中心的協力廠商服務提供者（如Amazon Web Service、Microsoft Azure 或 Google Cloud）提供，他們擁有實體伺服器硬體，然後通過安全的互聯網連接線上銷售這些資源。在私有雲中，企業通過虛擬伺服器上運行任意數量的可用實體電腦上的應用程式，在自己的資料中心內構建雲。混合雲運算則是私有雲運算和公有雲雲算服務混合使用。作為 RightScale's 2018 State of the Cloud report的一部分，針對 997 名 IT 專業人員進行了深入調查，瞭解他們採用雲基礎架構和相關技術，有96% 的受訪者表示，在運行企業的各種服務時都使用了雲端運算的技術，不管是公有雲、私有雲或是混和雲。
超融合基礎架構是什麼？ 超融合基礎架構（Hyper-Converged Infrastructure），是一種整合了儲存裝置及虛擬運算的資訊基礎架構框架。運用超融合式基礎架構 (HCI)，可將運算、儲存與網路結合成單一系統。這套簡化的解決方案會使用軟體和 x86架構伺服器來取代專用硬體，讓您能夠簡化作業、降低總持有成本並迅速擴充。HCI通過管理程序平台執行，例如VMware vSAN，KVM或Microsoft Hyper-V，用於虛擬化運算，軟件定義存儲和虛擬化網路。HCI通常在配備有直連式儲存（DAS）的標準伺服器上運作。
虛擬機器是什麼？ 虛擬機器（Virtual Machine）是一種軟體電腦，可以像實體電腦一樣執行作業系統和應用程式。虛擬機器由一組規格和組態檔組成，並由主機實體資源支援。每台虛擬機器都擁有可提供與實體硬體功能相同的虛擬裝置，這些裝置更易於攜帶、管理，且更加安全。
有任何想法，我們都很樂意協助您實現
聯絡我們
Please send us your idea
/ 1000
* For services and supports, please visit eSupport.
* We collect your information in accordance with our Privacy Policy.
Submitted Successfully
Submission Successful
