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Building a GPU cluster for AI

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Lambda

Whitepaper: https://lambdalabs.com/gpu-cluster/echelon

Learn, from start to finish, how to build a GPU cluster for deep learning. We’ll cover the entire process, including cluster level design, rack level design, node level design, CPU and GPU selection, power distribution, storage, and networking.

This talk is based on the Lambda Echelon GPU Cluster whitepaper. The whitepaper can be found above.

Slides for the talk can be found here:
http://files.lambdalabs.com/How%20to%20build%20a%20GPU%20cluster%20from%20scratch%20for%20your%20ML%20team.pdf

Errata:
– Slide 46 contains an erroneous diagram with a connection from the storage server to the compute fabric network, the storage server does not connect ot the compute fabric network. The correct diagram is available in the whitepaper.

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15 thoughts on “Building a GPU cluster for AI”

  5. Our group ordered around 10 lambda PCs 1 year ago. Right now more than 5 have problems. Some of them do not start up. Mine gets stuck randomly….

  6. Lots and lots of A100 GPUs. Every single one of them is a monster, almost 2x faster memory than the next best GPU. An entire room full of A100 racks… holy cow.

  10. Its nice to see a holistic explanation of designing / building / installing a complex multi-rack system…As someone that has spent years working on both sides of the "analog/digital divide" (physical data center world / digital world's various segments), the un-sexy physical aspects of available rack space / power / cooling / floor loading / network uplink bandwidth are often overlooked (often assumed)…A semi arrives with a pallet: "Hey Carl, you can have this online in a couple days, right?"

  13. I just love this kind things. How do i can start this kind bussnes how i can find customer for like small node and start building up

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