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Compositional Performance Modeling of LLM Inference Clusters with Hierarchical KV Caching
Design-space exploration of LLM inference clusters requires predicting how hardware and serving policies interact with hierarchical key-value (KV) caching. Isolated operation profiles alone do not determine cluster latency: reuse changes computational demand, while KV location, capacity, and content
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