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Re:AWS doesn't make sense for scientific computing by lostmsu on Friday October 07, 2022 @12:30PM (#33123540)
Any particular you could recommend for GPU?
Re:AWS doesn't make sense for scientific computing by theblazehen on Friday October 07, 2022 @12:47PM (#33123795)
Re:AWS doesn't make sense for scientific computing by dkobran on Friday October 07, 2022 @12:50PM (#33123851)
There are several tier-two clouds that offer GPUs but I think they generally fall prey to the many of the same issues you'll find with AWS. There is a new generation of accelerator native clouds e.g. Paperspace (https://paperspace.com) that cater specifically to HPC, AI, etc. workloads. The main differentiators are: - much larger GPU catalog - support for new accelerators e.g. Graphcore IPUs - different pricing structure that address problematic areas for HPC such as egress

However, one of the most important differences is the lack of unrelated web services related components that pose a major distraction/headache to users that don't have a DevOps background (which AWS obviously caters to). AWS can be incredibly complicated. Simple tasks are encumbered by a whole host of unrelated options/capabilities and the learning curve is very steep. A platform that is specifically designed to serve the scientific computing audience can be much more streamlined and user-friendly for this audience.

Disclosure: I work on Paperspace.

Re:AWS doesn't make sense for scientific computing by sabalaba on Friday October 07, 2022 @01:11PM (#33124150)
Lambda GPU Cloud has the cheapest A100s of that group. https://lambdalabs.com/service/gpu-cloud

Lambda A100s - $1.10 / hr Paperspace A100s - $3.09 / hr Genesis A100s - no A100s but their 3090 (1/2 the speed of 100) is - $1.30 / hr for half the speed

Re:AWS doesn't make sense for scientific computing by lostmsu on Friday October 07, 2022 @02:09PM (#33124940)
That's still way too expensive. 3090 is less than 2x of the monthly cost in Genesis. A100 is priced better here.
Re:AWS doesn't make sense for scientific computing by zatarc on Friday October 07, 2022 @01:25PM (#33124355)
I'm not in a position to recommend or not a particular provider for gpu-equipped servers, simply because I've never had the need for gpus.

My first thought was related to colocation services. From what I understand, a lot of people avoid on-premise/in-house solutions because they don't want to deal with server rooms, redundant power, redundant networks, etc.

So people go to the cloud and pay horrendous prices there.

Why not take a middle path? Build your own custom server with your perferred hardware and put in a colocation

Re:AWS doesn't make sense for scientific computing by latchkey on Friday October 07, 2022 @01:28PM (#33124393)
Coreweave. I know the CTO. They are doing great work over there.

https://www.coreweave.com

Re:AWS doesn't make sense for scientific computing by tryauuum on Friday October 07, 2022 @02:55PM (#33125456)
datacrunch.io has some 80G A100s