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Vectordash: GPU instances for deep learning
- jsty 8y agoWhat's your licensing situation with Nvidia regards their prohibition [1] on datacenter deployment for 'consumer' cards? [1] https://news.ycombinator.com/item?id=16002068 https://news.ycombinator.com/item?id=16002068
- disgruntledphd2 8y agoI have no real idea but sometimes its better to ask forgiveness rather than permission (i'm not in any way associated with this service).
- yorwba 8y agoIt does not sound like they are deploying in datacenters: https://vectordash.com/hosting/ https://vectordash.com/hosting/ That said, the license also has this: No Sublicensing or Distribution. Customer may not sell, rent, sublicense, distribute or transfer the SOFTWARE; or use the SOFTWARE for public performance or broadcast; or provide commercial hosting services with the SOFTWARE. which seems to prohibit Vectordash's individual hosts from participating.
- jsty 8y agoAh right, hadn't seen that. Thanks! If the vectordash team are reading, I'd make the nature of the service a bit clearer to potential users. There's no mention I can find outside the 'hosting' page that these aren't your machines.
- Samin100 8y agoGotcha! I’ll update the copy to make that a bit clearer.
- ctlaltdefeat 8y agoIf I understand correctly, the instances available are containerized instances that users run (i.e, the system matches hosts to guests and takes a cut). Beyond being dangerous on multiple levels, there doesn't seem to be any guarantee of storage or network bandwidth/traffic. Having a multi-TFLOP GPU to train with is hardly useful if you can't get the training data on the device in a reasonable amount of time, or hold that data in local storage.
- Samin100 8y agoWe ensure each instance has ample storage (min 50GB), internet speeds, and hardware specs such that the GPU is the bottleneck! If a user isn’t satisfied with an instance, then there’s no charge whatsoever :)
- jcims 8y agoWith 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?
- Samin100 8y agoJust read a pretty interesting paper on just this recently - we actually load/unload the drivers for every instance, which in turn also wipes the GPU’s memory. There’s a tool I wrote to test just this, albeit I haven’t uploaded it to GitHub yet. Might do that sometime this weekend.
- jcims 8y agoDo you happen to recall the title of the paper? Would be interested (in the utility as well if you do happen to upload it to github) Thanks!
- Samin100 8y agoYes! Here’s a link to the paper: http://www.eurecom.fr/fr/publication/4205/download/rs-publi-4205_1.pdf http://www.eurecom.fr/fr/publication/4205/download/rs-publi-...