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Dell is selling NVIDIA V100s for only about $20,000 for "home use". http://www.dell.com/en-us/work/shop/accessories/apd/490-bedx http://www.dell.com/en-us/work/

Dell is selling NVIDIA V100s for only about $20,000 for "home use". http://www.dell.com/en-us/work/shop/accessories/apd/490-bedx http://www.dell.com/en-us/work/shop/accessories/apd/490-bedx At its priciest in GCP ($2.48/hr) that's still about 7800 hours before buying was an advantage (15700 hours on preemptible gear). (Disclosure: I work at Google, but this is all public math)

leeoniya 8y ago
> Dell is selling NVIDIA V100s for only about $20,000 for "home use". or... https://www.thinkmate.com/product/nvidia/900-2g500-0000-000 https://www.thinkmate.com/product/nvidia/900-2g500-0000-000
- theDoug 8y ago
  You just saved the parent commentor $10k. I hope he gives you a commission from the savings!
- KaoruAoiShiho 8y ago
  If it's actually home use you can buy the Quadro gv100 for 8999 on the nvidia store: https://www.nvidia.com/en-us/design-visualization/quadro-store/ https://www.nvidia.com/en-us/design-visualization/quadro-sto...
  - scottlegrand2 8y ago
    Or a TitanV for $3000 because Tesla is more branding than anything else.
jacquesm 8y ago
Even at that price that's less than a year for continuous use and I'm sure that NVIDIA would be happy to make you a deal if you ordered enough of them. Now if you needed a few 100 of them for two weeks or so that would be a different matter.
- IntelMiner 8y ago
  7800 hours = 325 days It's -barely- less than a year, with 24/7 usage
  - jacquesm 8y ago
    And the price is vastly inflated. More likely you will end up sub $10K, which makes your payback with continuous use about 180 days. And typically people that are busy with ML will buy these cards because they intend to use them full time. Model training takes insane amounts of computing power.
KaoruAoiShiho 8y ago
Can you explain to us exactly how fast TPUv3 is compared to v2? There's been some confusion over how much of the increase is per chip vs sticking more chips in a pod.
- theDoug 8y ago
  Definitely not my job to spill beans on performance of a just-announced thing but details will definitely come. I also hope to see a lot of public clarity over this stuff. "More powerful" is incredibly vague and could literally mean just consumes more power. $/time to train models that other chipsets can will be a thing I advocate for transparency with.
throwaway2016a 8y ago
I saw a neat app idea that lets you crowdsource response time. I bet there are a lot of people that would gladly pay, say $10k, but personally $20k is too steep. I also don't know where this sits in relation to power and efficiency. Just because it costs Nvidia a small fortune doesn't mean someone else can't do it cheaper. Especially if the chip is laser focused to a specific instruction set (vs being a general purpose video card GPU -- which I'm not sure if the Nvidia one is). I assume from your response (and your disclosure) that is not the case though.

leeoniya 8y ago

> Dell is selling NVIDIA V100s for only about $20,000 for "home use". or... https://www.thinkmate.com/product/nvidia/900-2g500-0000-000 https://www.thinkmate.com/product/nvidia/900-2g500-0000-000

theDoug 8y ago
You just saved the parent commentor $10k. I hope he gives you a commission from the savings!
KaoruAoiShiho 8y ago
If it's actually home use you can buy the Quadro gv100 for 8999 on the nvidia store: https://www.nvidia.com/en-us/design-visualization/quadro-store/ https://www.nvidia.com/en-us/design-visualization/quadro-sto...
- scottlegrand2 8y ago
  Or a TitanV for $3000 because Tesla is more branding than anything else.

jacquesm 8y ago

Even at that price that's less than a year for continuous use and I'm sure that NVIDIA would be happy to make you a deal if you ordered enough of them. Now if you needed a few 100 of them for two weeks or so that would be a different matter.

IntelMiner 8y ago
7800 hours = 325 days It's -barely- less than a year, with 24/7 usage
- jacquesm 8y ago
  And the price is vastly inflated. More likely you will end up sub $10K, which makes your payback with continuous use about 180 days. And typically people that are busy with ML will buy these cards because they intend to use them full time. Model training takes insane amounts of computing power.

KaoruAoiShiho 8y ago

Can you explain to us exactly how fast TPUv3 is compared to v2? There's been some confusion over how much of the increase is per chip vs sticking more chips in a pod.

theDoug 8y ago
Definitely not my job to spill beans on performance of a just-announced thing but details will definitely come. I also hope to see a lot of public clarity over this stuff. "More powerful" is incredibly vague and could literally mean just consumes more power. $/time to train models that other chipsets can will be a thing I advocate for transparency with.

throwaway2016a 8y ago

I saw a neat app idea that lets you crowdsource response time. I bet there are a lot of people that would gladly pay, say $10k, but personally $20k is too steep. I also don't know where this sits in relation to power and efficiency. Just because it costs Nvidia a small fortune doesn't mean someone else can't do it cheaper. Especially if the chip is laser focused to a specific instruction set (vs being a general purpose video card GPU -- which I'm not sure if the Nvidia one is). I assume from your response (and your disclosure) that is not the case though.