Push-based KV transfer to improve TTFT and TPOT for disaggregated inference in vLLM
vLLM's prefill-decode disaggregation splits LLM inference across engine instances but must transfer the KV cache between them. This post introduces a push-based NIXL connector that moves transfer coordination off the critical path, delivering up to 3x better TTFT and 30% better TPOT in benchmarks on Amazon EC2 P5en instances with AWS EFA.
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Ce qui s'est passé
vLLM's prefill-decode disaggregation splits LLM inference across engine instances but must transfer the KV cache between them. This post introduces a push-based NIXL connector that moves transfer coordination off the critical path, delivering up to 3x better TTFT and 30% better TPOT in benchmarks on Amazon EC2 P5en instances with AWS EFA.
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The development may change operating conditions or market expectations around Amazon. Further confirmation and measurable outcomes matter.
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1 articles · 1 publication d'origine · 1 independantes
- AWS Machine Learning BlogSource primaire · Confirme · EN · 100%Push-based KV transfer to improve TTFT and TPOT for disaggregated inference in vLLM ↗
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