prefix caching
AI infra interview questions tagged prefix caching, across every topic.
6 questions · 1 unlocked for you
Concepts behind "prefix caching"
Review the concepts used in these questions.
Foundational
vLLM Server Arguments That MatterSeparate executor memory, allocated cache pools and logical occupancy. Map context, sequence and token-batch limits to the constraints they control, then tune a pinned deployment against per-rank memory and latency.🧮 Open Weights & Serving Engines
Foundational
SGLang Server Arguments That MatterTune static memory, prefill chunks and admission against measured workload behavior. Separate offline throughput heuristics from interactive queue budgets, and calculate the part of request work that prefix caching can save.🧮 Open Weights & Serving Engines
Advanced
Prefix Caching and KV ReusePrefix caching reuses compatible attention state for leading tokens. Calculate shared memory and token reuse, then weigh cache identity, block ownership and routing delay before expecting a latency gain.🚀 Inference & Serving🔒 Premium
Advanced
Request Routing and Load Balancing for LLMsAn LLM router chooses a compatible replica, weighing queue time against reusable prompt state. Cached work helps only when the extra wait does not erase the saving.📐 AI Systems Design🔒 Premium
Advanced
The Serving Optimization WaterfallTune an LLM deployment one change at a time against one fixed workload, in an order that follows the binding constraint. A measured run went from 789 to 6,568 output tokens per second, and the two biggest wins were not the knobs people usually reach for first.🚀 Inference & Serving🔒 Premium
Advanced
Hybrid State Checkpoints and RollbackA hybrid model must restore attention history and recurrent state to the same token boundary. Learn why a cache hit can require replay, how rejected draft tokens corrupt an in-place state, and what saved checkpoints cost.🚀 Inference & Serving🔒 Premium