Continuous Batching Beats Static and Dynamic by Up to 2.91× in vLLM
For anyone running an inference server: a zero-variance control, five traffic traces, and an engine-vs-scheduler split show where the gains come from. The post Continuous Batching Beats Static and Dynamic by Up to 2.91× in vLLM appeared first on Towards Data Science.
For anyone running an inference server: a zero-variance control, five traffic traces, and an engine-vs-scheduler split show where the gains come from. The post Continuous Batching Beats Static and Dynamic by Up to 2.91× in vLLM appeared first on Towards Data Science.
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