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arXiv · 2506.06122

Reinforcement Learning Optimization for Large-Scale Learning: An Efficient and User-Friendly Scaling Library

Weixun Wang·Shaopan Xiong·Gengru Chen·Wei Gao·Sheng Guo·Yancheng He·Ju Huang·Jiaheng Liu·Zhendong Li·Xiaoyang Li·Zichen Liu·Haizhou Zhao·Dakai An·Lunxi Cao·Qiyang Cao·Wanxi Deng·Feilei Du·Yiliang Gu·Jiahe Li·Xiang Li·Mingjie Liu·Yijia Luo·Zihe Liu·Yadao Wang·Pei Wang·Tianyuan Wu·Yanan Wu·Yuheng Zhao·Shuaibing Zhao·Jin Yang·Siran Yang·Yingshui Tan·Huimin Yi·Yuchi Xu·Yujin Yuan·Xingyao Zhang·Lin Qu·Wenbo Su·Wei Wang·Jiamang Wang·Bo Zheng
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Abstract

We introduce ROLL, an efficient, scalable, and user-friendly library designed for Reinforcement Learning Optimization for Large-scale Learning. ROLL caters to three primary user groups: tech pioneers aiming for cost-effective, fault-tolerant large-scale training, developers requiring flexible control over training workflows, and researchers seeking agile experimentation. ROLL is built upon several key modules to serve these user groups effectively. First, a single-controller architecture combined with an abstraction of the parallel worker simplifies the development of the training pipeline. Second, the parallel strategy and data transfer modules enable efficient and scalable training. Third, the rollout scheduler offers fine-grained management of each sample's lifecycle during the rollout stage. Fourth, the environment worker and reward worker support rapid and flexible experimentation with agentic RL algorithms and reward designs. Finally, AutoDeviceMapping allows users to assign resources to different models flexibly across various stages.

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Weixun Wang, Shaopan Xiong, Gengru Chen, Wei Gao, Sheng Guo, Yancheng He, Ju Huang, Jiaheng Liu, Zhendong Li, Xiaoyang Li, Zichen Liu, Haizhou Zhao, Dakai An, Lunxi Cao, Qiyang Cao, Wanxi Deng, Feilei Du, Yiliang Gu, Jiahe Li, Xiang Li, Mingjie Liu, Yijia Luo, Zihe Liu, Yadao Wang, Pei Wang, Tianyuan Wu, Yanan Wu, Yuheng Zhao, Shuaibing Zhao, Jin Yang, Siran Yang, Yingshui Tan, Huimin Yi, Yuchi Xu, Yujin Yuan, Xingyao Zhang, Lin Qu, Wenbo Su, Wei Wang, Jiamang Wang, Bo Zheng. 2025-06-06. Reinforcement Learning Optimization for Large-Scale Learning: An Efficient and User-Friendly Scaling Library. https://arxiv.org/abs/2506.06122

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