LLM推理系统问答

题集来源:阿东玩 AI(Adong)收录项目:AgentGuide查看原题集

题目目录

70 道原题
  1. How would you debug a sudden TTFT p99 spike in a production LLM serving system?

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  2. What is goodput and why is it more meaningful than raw throughput or individual metric SLO compliance?

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  3. How would you design an A/B testing framework for comparing two LLM versions in production?

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  4. Explain how you would capacity plan for an LLM serving system expecting 10× user growth in 6 months.

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  5. How would you measure and improve Model FLOP Utilization (MFU)?

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  6. How do diffusion language models generate text differently from autoregressive models? What are the inference implications?

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  7. What is Mixture of Depths? How does it enable adaptive inference compute?

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  8. Why might photonic computing change LLM inference fundamentally? What are the current limitations?

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  9. How does multi-token prediction improve both training and inference efficiency?

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  10. Describe an “inference-first” model design philosophy. What architectural choices reflect this approach?

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