Change default gpu metric backend #2501
Closed
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
FindHao
temporarily deployed
to
docker-s3-upload
GitHub Actions
Inactive
FindHao
had a problem deploying
to
docker-s3-upload
GitHub Actions
Error
FindHao
had a problem deploying
to
docker-s3-upload
GitHub Actions
Failure
|
Sorry, mixed with some other commits. will update it later. |
FindHao
force-pushed
the
findhao/operatorbench7
branch
from
4a9920d
to
2dd6ca9
Compare
FindHao
had a problem deploying
to
docker-s3-upload
GitHub Actions
Error
FindHao
had a problem deploying
to
docker-s3-upload
GitHub Actions
Failure
FindHao
had a problem deploying
to
docker-s3-upload
GitHub Actions
Error
resolved |
FindHao
temporarily deployed
to
docker-s3-upload
GitHub Actions
Inactive
FindHao
had a problem deploying
to
docker-s3-upload
GitHub Actions
Error
FindHao
had a problem deploying
to
docker-s3-upload
GitHub Actions
Failure
|
How about we make |
FindHao
temporarily deployed
to
docker-s3-upload
GitHub Actions
Inactive
done in 4398557 |
FindHao
had a problem deploying
to
docker-s3-upload
GitHub Actions
Failure
FindHao
temporarily deployed
to
docker-s3-upload
GitHub Actions
Inactive
6 tasks
FindHao
changed the title
torch 
xuzhao9
reviewed
Oct 11, 2024
userbenchmark/triton/run.py
Outdated
| parser.add_argument( | ||
| "--metrics-gpu-backend", | ||
| choices=["default", "nvml"], | ||
| default="default", |
There was a problem hiding this comment.
Let's change the default mode name to torch for readability.
xuzhao9
reviewed
Oct 11, 2024
run.py
Outdated
| @@ -477,18 +477,17 @@ def main() -> None: | |||
| ) | |||
| parser.add_argument( | |||
| "--metrics-gpu-backend", | |||
| choices=["dcgm", "default"], | |||
| choices=["dcgm", "default", "nvml"], | |||
There was a problem hiding this comment.
Same here, let's change the default backend name to torch
FindHao
temporarily deployed
to
docker-s3-upload
GitHub Actions
Inactive
FindHao
temporarily deployed
to
docker-s3-upload
GitHub Actions
Inactive
FindHao
had a problem deploying
to
docker-s3-upload
GitHub Actions
Failure
|
@FindHao has imported this pull request. If you are a Meta employee, you can view this diff on Phabricator. |
FindHao
temporarily deployed
to
docker-s3-upload
GitHub Actions
Inactive
FindHao
temporarily deployed
to
docker-s3-upload
GitHub Actions
Inactive
FindHao
had a problem deploying
to
docker-s3-upload
GitHub Actions
Failure
|
@FindHao has imported this pull request. If you are a Meta employee, you can view this diff on Phabricator. |
FindHao
temporarily deployed
to
docker-s3-upload
GitHub Actions
Inactive
FindHao
temporarily deployed
to
docker-s3-upload
GitHub Actions
Inactive
FindHao
had a problem deploying
to
docker-s3-upload
GitHub Actions
Failure
|
@FindHao has imported this pull request. If you are a Meta employee, you can view this diff on Phabricator. |
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.
The current GPU memory metric backend includes dcgm and nvml. They are reported from hardware and should be accurate. This PR adds the native torch way to collect GPU memory usage. It uses
torch.cuda.max_memory_allocated(). The benefit is that it has lower overhead and is accurate on a shared GPU server when there are mutliple GPU processes from other users. It is because we don't implement the process filter for the other two backends.Use
--metrics-gpu-backend torchto set the backend.