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Vectordash: GPU instances for deep learning

45 pointsby frlnBorgabout 7 years ago

3 comments

jstyabout 7 years ago
What&#x27;s your licensing situation with Nvidia regards their prohibition [1] on datacenter deployment for &#x27;consumer&#x27; cards?<p>[1] <a href="https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=16002068" rel="nofollow">https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=16002068</a>
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ctlaltdefeatabout 7 years ago
If I understand correctly, the instances available are containerized instances that users run (i.e, the system matches hosts to guests and takes a cut).<p>Beyond being dangerous on multiple levels, there doesn&#x27;t seem to be any guarantee of storage or network bandwidth&#x2F;traffic. Having a multi-TFLOP GPU to train with is hardly useful if you can&#x27;t get the training data on the device in a reasonable amount of time, or hold that data in local storage.
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jcimsabout 7 years ago
With more GPU-in-the-cloud offerings coming on line, is there a utility to dump GPU memory to see if your cloud provider has wiped it between customers?
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