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Learn how to efficiently use GPU acceleration for AI/ML

VMware vSphere Bitfusion virtualizes Graphics processing units (GPU) to provide a pool of shared, network-accessible GPU resources that support Artificial Intelligence (AI) and Machine Learning (ML) applications. Check out this demo-video to get an understanding about Bitfusion and how it helps to efficiently utilize GPU devices.

An Introduction to vSphere Bitfusion
November 11, 2020
This video details how vSphere Bitfusion helps to remote GPU devices for efficient use for AI/ML applications.

Solution

  • AI/ML

Type

  • Video

Level

  • Intermediate

Category

  • Feature Walk-through

Product

  • vSphere

Technology

  • Bitfusion

Latest Content

Bitfusion Compatibility and Interoperability
December 08, 2020
Provides Bitfusion compatibility details on driver &library versions, ML frameworks versions, operating systems, and hardware.

Solution

  • AI/ML
  • Application Acceleration
  • Modern Applications

Type

  • Document

Level

  • Intermediate

Category

  • Deployment Considerations

Product

  • vSphere
  • vSphere 6.5
  • vSphere 6.7
  • vSphere 7

Technology

  • Bitfusion

Phase

  • Design
  • Deploy
Using Assignable Hardware with Dynamic DirectPath IO
November 16, 2020
This video covers the new Assignable Hardware framework with Dynamic DirectPath I/O in vSphere 7. A new, flexible, way of utilizing hardware accelerators like GPU, FPGA, or NICs with virtual workloads. We'll demo how to configure virtual machines with a GPU using Dynamic DirectPath I/O.

Solution

  • AI/ML

Type

  • Video

Level

  • Advanced

Category

  • Technical Overview

Product

  • vSphere 7

Technology

  • Assignable Hardware
  • Hardware Acceleration

Phase

  • Deploy
Running Multiple Applications on One GPU with vSphere Bitfusion
November 12, 2020
Describes how Bitfusion can help you achieve the most efficient use of GPUs by partitioning its memory and running multiple concurrent applications, one in each partition. VMware vSphere Bitfusion also allows you do this while accessing the GPUs from remote servers.

Solution

  • AI/ML

Type

  • Blog

Level

  • Intermediate

Category

  • Best Practice
  • Proof of Concept

Product

  • vSphere
  • vSphere 6.7
  • vSphere 7

Technology

  • Bitfusion

Phase

  • Deploy
  • Optimize
Bitfusion Client Service – The Bash in the Rue Morgue
November 11, 2020
Create a Bitfusion Client service; run ML applications on VMs with pre-allocated remote GPUs for acceleration; eliminate need to invoke Bitfusion on the command line

Solution

  • AI/ML
  • Application Acceleration

Type

  • Blog

Level

  • Intermediate

Category

  • Activity Path

Product

  • vSphere
  • vSphere 6.7
  • vSphere 7

Technology

  • Bitfusion

Phase

  • Design
An Introduction to vSphere Bitfusion
November 11, 2020
This video details how vSphere Bitfusion helps to remote GPU devices for efficient use for AI/ML applications.

Solution

  • AI/ML

Type

  • Video

Level

  • Intermediate

Category

  • Feature Walk-through

Product

  • vSphere

Technology

  • Bitfusion
Bitfusion Jupyter Integration—It’s Full of Stars
November 10, 2020
Instructions and example to create a Bitfusion kernel for Jupyter Notebooks. Run your AI/ML application with remote access to GPUs for acceleration using Bitfusion technology inside Jupyter

Solution

  • AI/ML

Type

  • Blog

Level

  • Intermediate

Category

  • Activity Path
  • Best Practice

Product

  • vSphere
  • vSphere 6.7
  • vSphere 7

Technology

  • Bitfusion

Phase

  • Deploy
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