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Any particular you could recommend for GPU?

theblazehen 4y ago
https://www.genesiscloud.com/ https://www.genesiscloud.com/ is pretty decent
dkobran 4y ago
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 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.
sabalaba 4y ago
Lambda GPU Cloud has the cheapest A100s of that group. https://lambdalabs.com/service/gpu-cloud 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
- lostmsu 4y ago
  That's still way too expensive. 3090 is less than 2x of the monthly cost in Genesis. A100 is priced better here.
zatarc 4y ago
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
latchkey 4y ago
Coreweave. I know the CTO. They are doing great work over there. https://www.coreweave.com https://www.coreweave.com
tryauuum 4y ago
datacrunch.io has some 80G A100s

https://www.genesiscloud.com/ https://www.genesiscloud.com/ is pretty decent

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 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.

sabalaba 4y ago

Lambda GPU Cloud has the cheapest A100s of that group. https://lambdalabs.com/service/gpu-cloud 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

lostmsu 4y ago
That's still way too expensive. 3090 is less than 2x of the monthly cost in Genesis. A100 is priced better here.

zatarc 4y ago

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

latchkey 4y ago

Coreweave. I know the CTO. They are doing great work over there. https://www.coreweave.com https://www.coreweave.com

tryauuum 4y ago

datacrunch.io has some 80G A100s