Vishnu,
I have an alpha cluster on GKE with GPU (project is whitelisted, running
1.7.8), but I am unable to schedule workloads that require GPUs:
[image: unnamed.png]
example YAML for reproducing this:
apiVersion: apps/v1beta1
kind: Deployment
metadata:
name: my-tf
labels:
app: tf
spec:
selector:
matchLabels:
app: tf
replicas: 1
template:
metadata:
labels:
app: tf
spec:
containers:
- image: tensorflow/tensorflow:latest-gpu
name: my-tf
ports:
- containerPort: 8888
resources:
limits:
* alpha.kubernetes.io/nvidia-gpu
<http://alpha.kubernetes.io/nvidia-gpu>: 1*
Am I missing something?
Thanks.
On Mon, Oct 23, 2017 at 11:00 PM 'Vishnu Kannan' via Kubernetes user
discussion and Q&A <kubernetes-users@googlegroups.com> wrote:
> Hey there, if you are trying out alpha experience for GPUs on GKE, please sign
> up via this form <https://goo.gl/forms/HR0Upm9w30DW8aIU2> and request
> access to the doc listed in the form. If you have issues with GKE after
> going through the user guide, please PM me and I'll help you out.
>
> On Mon, Oct 23, 2017 at 12:48 AM, <kt...@cogent.co.jp> wrote:
>
>> Hi Vishnu,
>>
>> I am also trying to run a GPU cluster on GKE. And also hitting
>> allocatable GPU = 0 problem. Can you please guide me?
>>
>> On Tuesday, October 17, 2017 at 6:36:20 AM UTC+9, Vishnu Kannan wrote:
>> > GPU support in kubernetes is moving out of tree using a new extension
>> mechanism called device plugins. Nvidia has published a GPU device plugin
>> recently that is expected to work with kubernetes v1.8.
>> >
>> >
>> > If you are on GCP, please reach out to me and I can share an official
>> alpha user guide for GPUs with k8s.
>> >
>> >
>> > On Mon, Oct 16, 2017 at 12:54 AM, <burtc...@gmail.com> wrote:
>> >
>> >
>> > Hi Vu Pham,
>> >
>> > My allocatable GPU number is 0.
>> >
>> > Can you advise how you overcome the issue?
>> >
>> > Thanks, Burt
>> >
>> >
>> >
>> >
>> >
>> > --
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