Unstable inference time
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- Dominant language
- C++
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Description
Hi!
I run yolo11 model inference for 1000 times in Tesla T4, but I found the time cost was very unstable.
From the cached records, I found most of the time cost was even and looked normal, but the normal ones were always interleaved with a few abnormal ones. For example, of the 1000 times inference records, most of the inference time cost was 2ms per image, but there were a few that cost 70ms per image.
I had tried to set a fixed card frequency but it didnt seem to work.
So can you help me with that? Thanks!
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Research direction
No files, tests, or entry points are named. Begin by reproducing the reported YOLO11 inference timing on a Tesla T4 across 1000 runs, including the fixed-frequency setup, then identify what conditions distinguish the 2 ms runs from the occasional 70 ms runs; done means explaining or resolving the latency variation.
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Assessment
- Tech stack
- cpp
- Domain
- machine-learning, performance
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100