Initial commit: obsidian to gitea
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phd/weekly-report/25/251102.md
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phd/weekly-report/25/251102.md
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Objectives
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- Auto distributed LLM inference config optimization
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Key Results
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- [2/10] Build the first version auto tuner system
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- [5/10] Check the current situation of parallelism config optimization
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- [4/10] Understand the possibility/challenges in LLM inference compute graph arrangement automatically
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- [0/10] Trace vLLM compute graph and data flow
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- [3/10] Implement a minimal Rust inference framework
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- [1/10] Define the IR for automatic optimization
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- [5/10] Profile different parallelism setup with real trace and analysis their difference
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- [0/10] Meta-analysis for the theory maximum improvement with heterogenous setup [offtrack]
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Last Week
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- [KR1] Design the auto tuner system structure and draw a figure.
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- [KR1] Write code for hardware prober and workload profiler.
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Next Week
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- Continue to build the system with config generator and config tuner.
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