吞吐最高提升300%！港中文开源Libra，RL训练提速2.5倍

TL;DR - Libra is an open-source resource-management system for agentic RL post-training that dynamically balances GPUs between rollout and training. It improves throughput by up to 300% and reduces time-to-reward by up to 2.5×.

• A global planner jointly optimizes training parallelism, rollout GPU allocation, and heterogeneous TP configurations.
• C-MLFQ uses runtime tool-return signals to route evolving trajectories to suitable TP buckets instead of predicting lengths upfront.
• An elastic hybrid GPU pool shifts capacity without rebuilding the core training topology or pausing training.
• On 48 A800 GPUs, Libra achieved 196–300% higher throughput than colocated verl across search, math, and coding-agent workloads.