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Comment by recuter | Hacker News Reader

  After spending $100k in a year.. After doing the math, We decided to purchase three workstations at a total cost of $17k. 

  One is a GPU-based workstation with two RTX 3090s and an Intel i9–12900 CPU, and another two workstations with 16 cores AMD Ryzen 5950X CPUs.

  It took us a few FTE days to set those up to our satisfaction with slurm, NFS, backups, and several other services.

  We noticed that our RTXs, although considered gaming cards, are comparable (if not better) in performance to Tesla V100, which some cloud providers rent at the staggering price of $3.06 an hour.

tl;dr - They did the math.

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They also had a static workload, with no changing requirements, or really any need for scalability.

They also had FTEs with experience to configure the systems (which for a lot of us technical people is a no-brainer, but if you had data scientists with no hardware experience, that might be different)

This worked for them, and I'm happy for them.. the cloud does not solve all problems... It's simply one hardware strategy you can pick.. it's important to review the options!

That’s ok.

If you need a pickup truck two weekends a year, rent. If you need to carry tools and stuff every day, buy!

> They did the math.

And bought 3 workstations instead of 3 servers.

IMHO the headline of "Why Enzymit Decided to Build its Own On-Prem HPC Infrastructure" is a bit... stretched.

This is how universities (or people from academic background) interpret...

They have a workload that is entirely dictated by their protein design etc. projects, not by external access to a web app. So "high performance" means doing a single definite task quickly (so they can *proceed to the next run), not scaling to many users and requests. If they need to scale, they first hire protein designers or the like and then they set up some new workstation, probably something different from existing ones for diversification and obsolescence reasons. No cattle.

Well, they do use slurm, so it's technically a HPC stack.

We noticed that our RTXs, although considered gaming cards, are comparable (if not better) in performance to Tesla V100

You don't buy Tesla cards because you care about maximizing operations pr second, you buy them because you care about operations pr KWh.

No, you buy tesla cards so Nvidia doesn't sue you and stop providing firmware.

That's a good point. 3090 RTX may be 1.5x faster than my Titan V, but Titan V consumes 2x less energy on the same load while being much older generation card.

Plus less energy consumption means less heat generated which means you can pack them tighter and you can spend less on cooling etc etc. At scale these things really add app.

Worth noting that using a gaming card for workloads like this would likely void the warranty.

No it doesn't

Isn't it right there in the fine print?

> Warranted Product is intended for consumer end user purposes only, and is not intended for datacenter use and/or GPU cluster commercial deployments ("Enterprise Use"). Any use of Warranted Product for Enterprise Use shall void this warranty. https://www.nvidia.com/en-us/support/warranty/

I must have read over that

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