Support GPUs in scale from 0 #401
Merged
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
|
Fixes #392 |
|
/lgtm |
|
cc: @vishh |
vishh
reviewed
Oct 18, 2017
There was a problem hiding this comment.
Keep in mind starting from v1.8, the resource name for GPUs is nvidia.com/gpu and it's not included in core k8s API. So this PR IIUC won't autoscaling clusters>1.8.1 since it's using the old resource name alpha.kubernetes.io/nvidia-gpu (apiv1.ResourceNvidiaGPU)
Merged
| @@ -182,6 +190,7 @@ func TestBuildAllocatableFromKubeEnv(t *testing.T) { | |||
| capacityMemory string | |||
| expectedCpu string | |||
| expectedMemory string | |||
| gcuCount int64 | |||
There was a problem hiding this comment.
Typo: This should be gpuCount.
yaroslava-serdiuk
pushed a commit
to yaroslava-serdiuk/autoscaler
that referenced
this pull request
Feb 22, 2024
Add enhancements template and script for table of contents
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
When scaling up from 0, read information about GPUs from instance template. This allows us to support scaling up a relevant NodeGroup from 0 when we have a pending pod that needs GPUs.