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vast you have to choose specific machines. gpudeploy routes to whatever resources are available. vast has a lot of bad machines with terrible PCIe lanes and ar
by icelancer 2y ago
vast you have to choose specific machines. gpudeploy routes to whatever resources are available.
vast has a lot of bad machines with terrible PCIe lanes and architecture you have to learn the hard way. Someone on HN wrote a script to run a test docker image on every machine and auto-tagged the machines' quality using their API, which is what I'd do if I was going to use vast seriously for compute.
- polygot 2y agoDo you have a link to that thread/Docker image? I would be very interested using it
- icelancer 2y agoI don't, sorry. I would love to use it as well, I should've bookmarked it! Also, I'm not sure the person opensourced it.
- lelanthran 2y ago>> Im also interested in what the differing factor is. > vast has a lot of bad machines with terrible PCIe lanes and architecture you have to learn the hard way. Wouldn't gpudeploy have exactly the same problem? How is it mitigated with gpudeploy?
- everforward 2y agoI think it's more of a business strategy issue than a technical one. I suspect it would be trivial for Vast or GPUDeploy to spin up a benchmarking job before allowing sales on that machine. I'm not an expert on PCIe lanes, but I would think the performance issues would be visible via bandwidth or latency on the lanes. It kind of makes sense to me, though. If I were looking for absolute reliability and was willing to pay for it, I'd just go to one of the many GPU cloud vendors. Likewise, I suspect anyone willing to really work on getting good performance would rather be a real provider or sub-provider than being part of this nebulous C2C GPU cloud.