Objectives
- Auto LLM inference config tuner

Key Results
- [2/10] Workload grouping methods
- [9/10] Build the first version auto tuner system
- [8/10] Check the current situation of parallelism config optimization
- [4/10] Understand the possibility/challenges in LLM inference compute graph arrangement automatically
- [1/10] Define the IR for automatic optimization
- [5/10] Profile different parallelism setup with real trace and analysis their difference

Last Week
- [KR1] Run benchmark for different workload classifications and prove that different classification method will shift the best config and different workload groups need different configs to maximize the goodput.
- [misc] Prepare for IPADS group meeting presentation.
- [misc] Prepare for the ChinaSys presentation.

Next Week
- Define the workload classification space and find the method to group workload.
