Hi,
Thank you for your hard work to build a GPU memory sharing package and to make it open for everyone.
I have tested locally with multiple processes with different kinds of scenarios. It's working fine as expected.
I went through the README file.
--
The Device Plugin runs on every GPU-enabled node in your Kubernetes cluster (currently it will fail on non-GPU nodes but that is OK) and manages a single GPU on every node. It consumes a single nvidia.com/gpu device and advertizes it as multiple (by default 10) nvshare.com/gpu devices. This means that up to 10 containers can concurrently run on the same physical GPU.
So, If we deploy the deployment files it will deploy on every GPU-enabled node, but I want to deploy in a specific node only for now. I was thinking of changing the matchLabels under the selector section to nodeSelector but I see matchLabels' name is using other places as well.
Could you please help me out to deploy the node specifically?
Hi,
Thank you for your hard work to build a GPU memory sharing package and to make it open for everyone.
I have tested locally with multiple processes with different kinds of scenarios. It's working fine as expected.
I went through the README file.
--
The Device Plugin runs on every GPU-enabled node in your Kubernetes cluster (currently it will fail on non-GPU nodes but that is OK) and manages a single GPU on every node. It consumes a single nvidia.com/gpu device and advertizes it as multiple (by default 10) nvshare.com/gpu devices. This means that up to 10 containers can concurrently run on the same physical GPU.
So, If we deploy the deployment files it will deploy on every GPU-enabled node, but I want to deploy in a specific node only for now. I was thinking of changing the
matchLabelsunder the selector section to nodeSelector but I see matchLabels' name is using other places as well.Could you please help me out to deploy the node specifically?