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Type: Epic
Resolution: Done
Priority: Normal
Fix Version/s: Alongside OpenShift 4.13, July Release for PSAP, July Release for PSAP - II, July Release for PSAP - III, July Release for PSAP - IV, July Release for PSAP - V, July Release for PSAP - VI, July Release for PSAP - VII, July Release for PSAP - VIII
Affects Version/s: None
Component/s: AI/ML
Labels:
- AI/ML
- no-feature

Epic Name:
Power measurement for AI/ML inference
Blocked:
False
Blocked Reason:
None
Ready:
False
Color Status:
Not Selected
Epic Status:
To Do
Flagged:

Impediment
Hierarchy Progress:
100
Hierarchy Progress Bar:

100% 100%

SFDC Cases Links:
SFDC Cases Counter:

Intelligence Requested:
Market:

Epic Goal

Measure/monitor/characterize the power usage and performance of AI/ML inference workloads like MLPerf Inference

Why is this important?

Gain experience and develop workflows for measuring power usage of workloads running on OCP.
Publish a blog post about running Inference workloads on OpenShift, building on Anisha's internship project

Acceptance Criteria

Open questions::

…

Done Checklist

1.	Docs Tracker		Closed		Ashish Kamra
2.	PX Tracker		Closed		Ashish Kamra
3.	QE Tracker		Closed		Ashish Kamra
4.	TE Tracker		Closed		Ashish Kamra

Assignee:: David Gray

Reporter:: David Gray

Votes:: 0 Vote for this issue

Watchers:: 3 Start watching this issue

Created:: 2023/01/26 8:54 PM

Updated:: 2023/07/18 3:02 PM

Resolved:: 2023/07/14 6:56 PM