A Survey of Efficient LLM Inference Serving
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The curator’s take
This survey reviews recent advancements in optimizing LLM inference, addressing memory and computational bottlenecks. It covers instance-level techniques (like model placement and request scheduling), cluster-level strategies (like GPU deployment and load balancing), and emerging scenario-specific solutions, concluding with future research directions.
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