NPU Timeline Generation Guide
Prerequisites
- Python environment
- Chrome browser (for visualization)
Implementation Steps
1. Code Modification
Register the subscriber
Add the following at the beginning of your program:
MsptiMetrics::register_subscriber();
Add tracing to ACLNN functions (work for msprof as well)
Insert the following macro in your ACLNN functions where you want to measure performance:
LLM_MSTX_RANGE();
Release the subscriber
Add this at the end of your program:
MsptiMetrics::release_subscriber();
2. Log Processing
After running your program, process the generated log file using the timeline script:
python npu_timeline.py -i custom_log.log -o custom_output.json
3. Visualization
Open Chrome browser Navigate to: chrome://tracing Load the generated JSON file: custom_output.json