Objectives
- Heterogenous parallelism in cluster
- EP design for inference performance [untracked]

Key Results
- [6/10] Profile vLLM to get compute graph
- [2/10] Understand the possibility/challenges in LLM inference compute graph arrangement automatically
- [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
- [0/10] Understand how EP (static/dynamic) influence performance fully
- [4/10] Analysis correlations between MoE layers [suspended]

Last Week
- [KR2] Learn about triton (vLLM has many kernel implemented in triton), run a demo to compile the python triton kernel to get ptx then loaded and called in Rust.
- [KR2] Try a demo to run vLLM's flash-attention in Rust.

Next Week
- Find a way to get the full compute flow and data flow in vLLM, then replay in Rust.
