vSphere Bitfusion delivers elastic infrastructure for AI/ML workloads by creating pools of hardware accelerator resources, such as GPUs. VMware has acquired Bitfusion in late-2019 and it has been recently announced that Bitfusion will be an integrated feature of vSphere 7.0.
On the 36th episode of Virtual Stack Podcast, I'm joined by Mike Adams (Sr. Director Cloud Platform Product Marketing at VMware) and we discuss about vSphere Bitfusion, its technology and use cases.
Virtual Stack is available on all major apps: Apple Podcast, Spotify, Google Podcast, Stitcher and more. As usual, feel free to share your feedback via Twitter (@emregirici), LinkedIn or virtualstack.tech.
Show Notes:
01:00 - Intro
02:00 - Intro to Bitfusion and their technology
05:30 - Relationship between GPU technology and AI/ML applications
08:30 - How can we use Bitfusion, is it now a part of vSphere? How's pricing and packaging?
12:30 - The architecture and components of the solution
15:00 - What's CUDA and what's its relationship with Bitfusion technology?
19:15 - What about Kubernetes workloads and Bitfusion?
21:45 - What are some of the use cases/verticals that can benefit from Bitfusion technology?
30:15 - Usage of FPGA and custom ASICs with Bitfusion.
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