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I believe the author is referring to accessing the GPUs from VMs. i.e. if you have 16 core machine with a 1024 core GPU you can split it up so it looks like 4 m
by muizelaar 12y ago
I believe the author is referring to accessing the GPUs from VMs. i.e. if you have 16 core machine with a 1024 core GPU you can split it up so it looks like 4 machines with 4 cores and 256 core GPU.
The sentence that you snipped seems to refer to this. "Right now, this isn’t doable because cloud services don’t even have video cards in them typically (I’m looking at you Azure. I can’t use you for offloading Metamaps!)"
- wtallis 12y agoIt's already possible to partition GPUs to share them across multiple VMs. Intel's got modified versions of Xen and KVM to support this for Haswell and later IGPs, and AMD and NVidia both have proprietary solutions. Furthermore, this has nothing to do with rendering APIs; it's all in the driver and hypervisor.
- muizelaar 12y agoI have no doubt. I was just trying to clarify what the original author may have been intending to say.
- lmeyerov 12y agoYes, running the VM would be silly, but machine learning etc. is awesome. We get acces and time sharing across resources much easier (at all) now. At Graphistry, we are using AWS G2 instances for previously impossibly big interactive data visualizations and streaming into stock browsers. It's pretty ridiculously cool :) Always happy to chat about GPU clouds and related fun things.
- EpicEng 12y agoPerhaps, but that's not what the author said: "there’s nothing stopping a DirectX 12 enabled machine from fully running VMs on these video cards."