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An article explaining static, dynamic, and continuous batching strategies in LLM inference, and why serving LLMs differs from traditional ML inference.
This article explains static, dynamic, and continuous batching strategies for serving large language models on GPUs, detailing their trade-offs and how they optimize throughput and reduce idle time.