jd-opensource / jd-opensource/JoyAI-Video-Edit
High end-to-end latency on non-B200 GPUs
- Dominant language
- Python
- Stars
- 1.9k
- Forks
- 95
- Avg merge
- 1d 18m
- Merged PRs (30d)
- 1
Description
I found that when running on GPUs other than B200, the actual network/display latency becomes significantly higher.
Is there a way to optimize this for lower-end GPUs? Also, would it be possible to lower the FPS or reduce the number of frames processed per step to improve real-time responsiveness and reduce accumulated latency?
Contributor guide
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Research direction
The issue names no files, tests, or entry points. First reproduce the latency difference on a non-B200 GPU and compare network/display timing with B200; then locate the controls for FPS and frames processed per step. Done means lower-end GPUs show reduced accumulated latency without losing the intended real-time behavior.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning, performance
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Active
- Clarity
- Needs clarification
- Newbie friendliness
- 45/100