Cover Image

Laminar: A Scalable Asynchronous RL Post-Training Framework

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Sheng, Guangming, Tong, Yuxuan, Wan, Borui, Zhang, Wang, Jia, Chaobo, Wu, Xibin, Wu, Yuqi, Li, Xiang, Zhang, Chi, Peng, Yanghua, Lin, Haibin, Liu, Xin, Wu, Chuan
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence Distributed, Parallel, and Cluster Computing
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

QSync: Quantization-Minimized Synchronous Distributed Training Across Hybrid Devices
by: Zhao, Juntao, et al.
Published: (2024)

HybridFlow: A Flexible and Efficient RLHF Framework
by: Sheng, Guangming, et al.
Published: (2024)

LLM-PQ: Serving LLM on Heterogeneous Clusters with Phase-Aware Partition and Adaptive Quantization
by: Zhao, Juntao, et al.
Published: (2024)

SWIFT: Expedited Failure Recovery for Large-scale DNN Training
by: Zhong, Yuchen, et al.
Published: (2023)

Unleashing Efficient Asynchronous RL Post-Training via Staleness-Constrained Rollout Coordination
by: Li, Haoyang, et al.
Published: (2026)

Schedule-Level Shared-Prefix Reuse for LLM RL Training
by: Li, Pengbo, et al.
Published: (2026)

MSPipe: Efficient Temporal GNN Training via Staleness-Aware Pipeline
by: Sheng, Guangming, et al.
Published: (2024)

DistFlow: A Fully Distributed RL Framework for Scalable and Efficient LLM Post-Training
by: Wang, Zhixin, et al.
Published: (2025)

AReaL-Hex: Accommodating Asynchronous RL Training over Heterogeneous GPUs
by: Yan, Ran, et al.
Published: (2025)

RollMux: Phase-Level Multiplexing for Disaggregated RL Post-Training
by: Wu, Tianyuan, et al.
Published: (2025)

SAGIPS: A Scalable Asynchronous Generative Inverse Problem Solver
by: Lersch, Daniel, et al.
Published: (2024)

MegaScale-Data: Scaling Dataloader for Multisource Large Foundation Model Training
by: Zhao, Juntao, et al.
Published: (2025)

JUMBO: Fully Asynchronous BFT Consensus Made Truly Scalable
by: Cheng, Hao, et al.
Published: (2024)

TensorHub: Scalable and Elastic Weight Transfer for LLM RL Training
by: Ye, Chenhao, et al.
Published: (2026)

StreamRL: Scalable, Heterogeneous, and Elastic RL for LLMs with Disaggregated Stream Generation
by: Zhong, Yinmin, et al.
Published: (2025)

Heta: Distributed Training of Heterogeneous Graph Neural Networks
by: Zhong, Yuchen, et al.
Published: (2024)

HAP: SPMD DNN Training on Heterogeneous GPU Clusters with Automated Program Synthesis
by: Zhang, Shiwei, et al.
Published: (2024)

SP-MoE: Speculative Decoding and Prefetching for Accelerating MoE-based Model Inference
by: Chen, Liangkun, et al.
Published: (2025)

DiffusionPipe: Training Large Diffusion Models with Efficient Pipelines
by: Tian, Ye, et al.
Published: (2024)

DORA: A Scalable Asynchronous Reinforcement Learning System for Language Model Training
by: Hu, Tianhao, et al.
Published: (2026)

Scalable Analysis of Urban Scaling Laws: Leveraging Cloud Computing to Analyze 21,280 Global Cities
by: Li, Zhenhui, et al.
Published: (2024)

ATOM: Asynchronous Training of Massive Models for Deep Learning in a Decentralized Environment
by: Wu, Xiaofeng, et al.
Published: (2024)

AMDP: Asynchronous Multi-Directional Pipeline Parallelism for Large-Scale Models Training
by: Chen, Ling, et al.
Published: (2026)

ElasWave: An Elastic-Native System for Scalable Hybrid-Parallel Training
by: Kang, Xueze, et al.
Published: (2025)

SDSL-Solver: Scalable Distributed Sparse Linear Solvers for Large-Scale Interior Point Methods
by: Yang, Shaofeng, et al.
Published: (2026)

RollPacker: Mitigating Long-Tail Rollouts for Fast, Synchronous RL Post-Training
by: Gao, Wei, et al.
Published: (2025)

MegaScale-Omni: A Hyper-Scale, Workload-Resilient System for MultiModal LLM Training in Production
by: Xue, Chunyu, et al.
Published: (2026)

HexiSeq: Accommodating Long Context Training of LLMs over Heterogeneous Hardware
by: Liang, Yan, et al.
Published: (2026)

Robust LLM Training Infrastructure at ByteDance
by: Wan, Borui, et al.
Published: (2025)

PRISM: Probabilistic Runtime Insights and Scalable Performance Modeling for Large-Scale Distributed Training
by: Golden, Alicia, et al.
Published: (2025)

An Experimental Study of Different Aggregation Schemes in Semi-Asynchronous Federated Learning
by: Li, Yunbo, et al.
Published: (2024)

Lemonshark: Asynchronous DAG-BFT With Early Finality
by: Hu, Michael Yiqing, et al.
Published: (2026)

AsyncHZP: Hierarchical ZeRO Parallelism with Asynchronous Scheduling for Scalable LLM Training
by: Bai, Huawei, et al.
Published: (2025)

AsyncSC: An Asynchronous Sidechain for Multi-Domain Data Exchange in Internet of Things
by: Yang, Lingxiao, et al.
Published: (2024)

OrchMLLM: Orchestrate Multimodal Data with Batch Post-Balancing to Accelerate Multimodal Large Language Model Training
by: Zheng, Yijie, et al.
Published: (2025)

Role-Based Fault Tolerance System for LLM RL Post-Training
by: Chen, Zhenqian, et al.
Published: (2025)

VDCores: Resource Decoupled Programming and Execution for Asynchronous GPU
by: He, Zijian, et al.
Published: (2026)

Ordered Momentum for Asynchronous SGD
by: Shi, Chang-Wei, et al.
Published: (2024)

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing
by: Wang, Yanbo, et al.
Published: (2026)

Fides: Secure and Scalable Asynchronous DAG Consensus via Trusted Components
by: Xie, Shaokang, et al.
Published: (2025)