Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

[misc] add cuda runtime version to usage data #12190

Merged
merged 2 commits into from
Jan 21, 2025
Merged

[misc] add cuda runtime version to usage data #12190

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
bcdfe1d
add cuda runtime version to usage data
youkaichao Jan 19, 2025
054e3dd
Merge remote-tracking branch 'upstream/main' into driver_and_cuda
ywang96 Jan 20, 2025
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
3 changes: 3 additions & 0 deletions vllm/usage/usage_lib.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -130,6 +130,7 @@ def __init__(self) -> None:
self.total_memory: Optional[int] = None
self.architecture: Optional[str] = None
self.platform: Optional[str] = None
self.cuda_runtime: Optional[str] = None
Copy link
Member Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

also tried to add cuda driver version, but that seems quite complicated. we don't have an easy way to get it. I think cuda runtime version is enough right now.

self.gpu_count: Optional[int] = None
self.gpu_type: Optional[str] = None
self.gpu_memory_per_device: Optional[int] = None
Expand Down Expand Up @@ -169,6 +170,8 @@ def _report_usage_once(self, model_architecture: str,
self.gpu_count = torch.cuda.device_count()
self.gpu_type = device_property.name
self.gpu_memory_per_device = device_property.total_memory
if current_platform.is_cuda():
self.cuda_runtime = torch.version.cuda
self.provider = _detect_cloud_provider()
self.architecture = platform.machine()
self.platform = platform.platform()
Expand Down
Loading