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

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.