LLM Serving & Inference Infrastructure

Prefill vs decode, the KV cache, continuous batching, streaming, GPU capacity and cold starts, and model routing.

0 / 7 solved
0/7 solved
Question Tags Difficulty Success
1. Stuck Behind the Long One
continuous-batchingstatic-batching +1
Medium —
2. Slow Start, Smooth Finish
prefill-vs-decodetime-to-first-token +2
Medium —
3. Thirty Six Gigabytes
kv-cachegpu-memory +2
Medium —
4. Waiting On Request B
continuous-batchingiteration-level-scheduling +2
Medium —
5. Line Out the Door
queueing-for-inferenceload-shedding +1
Hard —
6. The Stream Stutters
chunked-prefillinter-token-latency +3
Hard —
7. Even The Oracle Wastes
paged-attentionmemory-fragmentation +2
Hard —

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7 of 7 questions here are still unsolved.