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obsidian/phd/weekly-report/25/251102.md

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Objectives
- Auto distributed LLM inference config optimization
Key Results
- [2/10] 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] Design the auto tuner system structure and draw a figure.
- [KR1] Write code for hardware prober and workload profiler.
Next Week
- Continue to build the system with config generator and config tuner.