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3V0-21.23 · Question #25

An organization's data scientists are executing a plan to use machine learning (ML). They must have access to graphical processing unit (GPU) capabilities to execute their computational models when…

The correct answer is A. NVIDIA vGPU E. vSphere Bitfusion. https://blogs.vmware.com/apps/2018/07/using-gpus-with-virtual-machines-on-vsphere-part-1-

Design for compute services

Question

An organization's data scientists are executing a plan to use machine learning (ML). They must have access to graphical processing unit (GPU) capabilities to execute their computational models when needed. The solutions architect needs to design a solution to ensure that GPUs can be shared by multiple virtual machines. Which two solutions should the architect recommend to meet these requirements- (Choose two.)

Options

  • ANVIDIA vGPU
  • BAMD MxGPU
  • CvSphere DirectPath I/O
  • DvSGA
  • EvSphere Bitfusion

How the community answered

(27 responses)
  • A
    70% (19)
  • B
    19% (5)
  • C
    7% (2)
  • D
    4% (1)

Explanation

https://blogs.vmware.com/apps/2018/07/using-gpus-with-virtual-machines-on-vsphere-part-1-

Topics

#GPU sharing#NVIDIA vGPU#vSphere Bitfusion#ML workloads

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