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Table of ContentsLab Overview - HOL-2047-91-ISM - Using Bitfusion GPU virtualization in vSphereLightning Lab .................................................................................................................... 2
Lab Guidance .......................................................................................................... 3Introduction............................................................................................................. 4Hands-on Labs Interactive Simulation: Using Bitfusion GPU virtualization invSphere................................................................................................................... 8Conclusion............................................................................................................... 9Appendix - Lab Guidance ...................................................................................... 11
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Lab Overview -HOL-2047-91-ISM - Using
Bitfusion GPUvirtualization in vSphere
Lightning Lab
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Lab GuidanceWelcome to the Using Bitfusion GPU virtualization in vSphere Lightning Lab.
We have developed Lightning Labs to help you learn about VMware products in smallsegments of time. In this lab, you will learn about Bitfusion FlexDirect and how a VMwithout a GPU can use the GPU on another VM.
Lab Captains:
• Uday Kurkure, Staff Engineer 1, USA• Kenyon Hensler, Global Solutions Consultant, USA. Uday Kurkure, Staff
Engineer 1, USA
Below are the lab modules included in the complete Machine Learning Workloads invSphere Using GPUs lab:
• Module 1 -Machine Learning Apps in vSphere VMs Using GPUs• Module 2 -Using NVIDIA GRID vGPUs in vSphere• Module 3 -Using GPUs in Pass-through Mode on vSphere• Module 4 -Using Bitfusion GPU virtualization in vSphere• Module 5 -Performing Infrastructure Maintenance when VMs are using
GPUs• Module 6 -Running Machine Learning Workloads using TensorFlow in
vSphere• Module 7 -vGPU Scheduling Options• Module 8 -Maximizing the Power of vSphere for Diverse Workloads using
GPUs
This lab manual can be downloaded from the Hands-on Labs Document site found here:
http://docs.hol.vmware.com
If you have never taken a lab, view the Appendix - Lab Guidance to see bestpractices and tips on how to use the lab environment console.
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IntroductionIn this module, you will learn about Bitfusion FlexDirect and how a VM without a GPUcan use the GPU on another VM.
Bitfusion FlexDirect is a GPU virtualization solution provided by a company namedBitfusion. The GPU accelerators can be shared over the network and accessed remotelyby VMs. With Bitfusion, GPU accelerators are now part of a common infrastructureresource pool and available for use by VMs in the vSphere-based environment.
Bitfusion FlexDirect runs as a userspace application within each VM instance, withoutthe need for change or special software in the ESXi hypervisor or the AI applications. Onthe GPU-accelerated server VM, FlexDirect also runs as a transparent software layer andexposes the individual physical GPUs as a pooled resource to be consumed by clientVMs (VMs don't have GPUs). Upon completion of the AI runtime code, the shared GPUresources go back into the resource pool.
Bitfusion use-cases on vSphere can be broadly categorized into 3 types.
Dynamic and Remote Attached GPUs
Bitfusion FlexDirect allows remote attach of GPUs dynamically to client VMs, as shown inFig 4.1. GPUs can also be dynamically detached after use.
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Fig 4.1 Dynamic and Remote Attached GPUs
Partial GPUs
Bitfusion FlexDirect can be used to slice GPUs to non-equal parts of partial GPUs. Thisserves as an optimal architecture for machine learning, in which each user/workloadtype is unpredictable and requires non-equal performance and response time. The GPUsare sliced with GPU memory. For instance, say there is a GPU with 16GB of GPU memory,one could create multiple partial GPUs namely two 4GB partial GPUs and four 2GBpartial GPUs using FlexDirect. This allows sharing the same GPU across multiple users ina multi-tenant environment, as shown in Fig 4.2.
• Fig 4.2 Bitfusion FlexDirect Partial GPUs. Here, vGPU means the memory slicedpartial GPU.
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Dynamic and Remote Attached Partial GPUs
Bitfusion FlexDirect can also be leveraged to remotely attach partial GPUs dynamically.A group of GPUs can be re-configured to partial GPUs of different size and combination,and can be remotely attached to client VMs, as shown in Fig 4.3.
• Fig 4.3 Bitfusion FlexDirect Remote Partial GPUs. Here, Virtual GPU means thememory sliced partial GPU.
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Summary
With VMware vSphere and Bitfusion, GPUs can be a shared pool of resources that can beattached to any VMs as shown in Fig 4.4. A full-fledged GPU as a Service can be createdwith VMWare vSphere and Bitfusion FlexDirect. FlexDirect GPU resource schedulers willbe started on all the GPU server VMs in the pool. Each of the Client VMs will useFlexDirect to attach full or partial remote GPUs from the GPU pool. For more information,you can check Bitfusion FlexDirect documentation https://docs.bitfusion.io
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Hands-on Labs Interactive Simulation:Using Bitfusion GPU virtualization invSphereThis part of the lab is presented as a Hands-on Labs Interactive Simulation. This willallow you to experience steps which are too time-consuming or resource intensive to dolive in the lab environment. In this simulation, you can use the software interface as ifyou are interacting with a live environment.
1. Click here to open the interactive simulation. It will open in a new browserwindow or tab.
2. When finished, click the “Return to the lab” link to continue with this lab.
The lab continues to run in the background. If the lab goes into standby mode, you canresume it after completing the module.
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ConclusionIn this lab, you have learned one of ways to use GPUs on vSphere byleveraging Bitfusion GPU virtualization solution.
You have finished the Bitfusion Lightning Lab.
Congratulations on completing the Lightning Lab!
If you are looking for additional information on Machine Learning at VMware, try one ofthese:
• Click on this https://blogs.vmware.com/apps/machine-learning-resources• Or use your smart device to scan the QRC Code.
Below are the lab modules included in the complete Machine Learning Workloads invSphere Using GPUs.
• Module 1 -Machine Learning Apps in vSphere VMs Using GPUs• Module 2 - Using NVIDIA GRID vGPUs in vSphere• Module 3 - Using GPUs in Pass-through Mode on vSphere• Module 4 - Using Bitfusion GPU virtualization in vSphere• Module 5 - Performing Infrastructure Maintenance when VMs are using GPUs• Module 6 - Running Machine Learning Workloads using TensorFlow in vSphere• Module 7 - vGPU Scheduling Options• Module 8 - Maximizing the Power of vSphere for Diverse Workloads using GPUs
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How to End Lab
To end your lab click on the END button.
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Appendix - Lab GuidanceLocation of the Main Console
1. The area in the RED box contains the Main Console. The Lab Manual is on the tabto the Right of the Main Console.
2. A particular lab may have additional consoles found on separate tabs in the upperleft. You will be directed to open another specific console if needed.
3. Your lab starts with 90 minutes on the timer. The lab can not be saved. All yourwork must be done during the lab session. But you can click the EXTEND toincrease your time. If you are at a VMware event, you can extend your lab timetwice, for up to 30 minutes. Each click gives you an additional 15 minutes.Outside of VMware events, you can extend your lab time up to 9 hours and 30
minutes. Each click gives you an additional hour.
Alternate Methods of Keyboard Data Entry
During this module, you will input text into the Main Console. Besides directly typing itin, there are two very helpful methods of entering data which make it easier to entercomplex data.
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Click and Drag Lab Manual Content Into Console ActiveWindow
You can also click and drag text and Command Line Interface (CLI) commands directlyfrom the Lab Manual into the active window in the Main Console.
Accessing the Online International Keyboard
You can also use the Online International Keyboard found in the Main Console.
1. Click on the Keyboard Icon found on the Windows Quick Launch Task Bar.
Click once in active console window
<div class="player-unavailable"><h1 class="message">An error occurred.</h1><div class="submessage"><ahref="http://www.youtube.com/watch?v=xS07n6GzGuo" target="_blank">Try watching this video on www.youtube.com</a>, or enableJavaScript if it is disabled in your browser.</div></div>
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In this example, you will use the Online Keyboard to enter the "@" sign used in emailaddresses. The "@" sign is Shift-2 on US keyboard layouts.
1. Click once in the active console window.2. Click on the Shift key.
Click on the @ key
1. Click on the "@ key".
Notice the @ sign entered in the active console window.
Activation Prompt or Watermark
When you first start your lab, you may notice a watermark on the desktop indicatingthat Windows is not activated.
One of the major benefits of virtualization is that virtual machines can be moved andrun on any platform. The Hands-on Labs utilizes this benefit and we are able to run thelabs out of multiple datacenters. However, these datacenters may not have identicalprocessors, which triggers a Microsoft activation check through the Internet.
Rest assured, VMware and the Hands-on Labs are in full compliance with Microsoftlicensing requirements. The lab that you are using is a self-contained pod and does nothave full access to the Internet, which is required for Windows to verify the activation.
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Without full access to the Internet, this automated process fails and you see thiswatermark.
This cosmetic issue has no effect on your lab.
Look at the lower right portion of the screen
Please check to see that your lab has finished all the startup routines and is ready foryou to start. If you see anything other than "Ready", please wait a few minutes. If after5 minutes your lab has not changed to "Ready", please ask for assistance.
Click here to return to the click VMware Cloud on AWS - Introduction
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ConclusionThank you for participating in the VMware Hands-on Labs. Be sure to visithttp://hol.vmware.com/ to continue your lab experience online.
Lab SKU: HOL-2047-91-ISM
Version: 20190926-121231
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