FastServe adds token-level preemption and a skip-join MLFQ scheduler to LLM serving, delivering up to 31.4x higher throughput than vLLM at equivalent average and tail latency.
Train big, then compress: Rethink- ing model size for efficient training and inference of transformers
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Fast Distributed Inference Serving for Large Language Models
FastServe adds token-level preemption and a skip-join MLFQ scheduler to LLM serving, delivering up to 31.4x higher throughput than vLLM at equivalent average and tail latency.