Prorsa: Unleashing the Potential of Prefill-Decode Disaggregation in Agentic Reinforcement Learning

Name: Prorsa: Unleashing the Potential of Prefill-Decode Disaggregation in Agentic Reinforcement Learning
Uploaded: 2026-10-18T18:42:03.911572+00:00
Duration: 1255 s
Description: Prorsa introduces an agentic RL framework that uses prediction-guided prefill-decode resource allocation to speed up rollout by 1.11x to 4.05x over traditional methods. It monitors trajectory lifecycles to forecast future inference demand and dynamically switches workers between prefill and decode roles, effectively mitigating interference and maximizing GPU utilization.

Prorsa introduces an agentic RL framework that uses prediction-guided prefill-decode resource allocation to speed up rollout by 1.11x to 4.05x over traditional methods. It monitors trajectory lifecycles to forecast future inference demand and dynamically switches workers between prefill and decode roles, effectively mitigating interference and maximizing GPU utilization.

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