Objectives
- Auto LLM inference config tuner

Key Results
- [4/10] Build the first version auto tuner system
- [5/10] Check the current situation of parallelism config optimization
- [4/10] Understand the possibility/challenges in LLM inference compute graph arrangement automatically
- [0/10] Trace vLLM compute graph and data flow
- [3/10] Implement a minimal Rust inference framework
- [1/10] Define the IR for automatic optimization
- [5/10] Profile different parallelism setup with real trace and analysis their difference
- [0/10] Meta-analysis for the theory maximum improvement with heterogenous setup [offtrack]

Last Week
- [KR1] Write code for basic config generator and benchmark to check the performance.
- [KR1] Trying to find a way to tune the config for better performance.

Next Week
- Benchmark for baseline and some human-tuned configs to prove the necessary of config tuning.
- Continue to design a way for auto tuning.