Resource Constraints Response Program
- Video Memory Allocation: Adjust the num_gpus parameter (e.g., 0.1) in ray_actor_options to achieve particle size assignment
- Model quantification: Set WhisperComputeType.INT8 to reduce compute precision for performance.
- batch: Split large video files into segments for processing
Configuration recommendations
- Select small model size (WhisperModelSize.SMALL)
- Enable CPU fallback mode (num_gpus=0)
- Limiting container resources when deploying with Docker
monitoring tool
Real-time monitoring via Ray Dashboard (http://127.0.0.1:8265):
- GPU Utilization
- memory consumption
- Task Queue Status
This answer comes from the articleAana SDK: An Open Source Tool for Easy Deployment of Multimodal AI ModelsThe
May not be reproduced without permission:AI productivity tools " How to optimize the performance of Aana SDK for limited GPU resources?
