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cs.DC2026
NeMo-DCR: Bit-Exact Delta-Compressed Refit for Scalable Agentic RL at Trillion-Parameter Scale
Songlin Jiang, Zhiyu Li, Terry Kong +5
Agentic reinforcement learning (RL) disaggregates training from rollout, so each policy update must reach the rollout clusters before the next batch. Transferring a full 1T checkpo…
cs.DC2026
NCCL M2N: A Layout- and Topology-Aware Collective for Distributed Tensor Resharding
Kaushik Kandadi, Youngeun Kwon, Sreeram Potluri +6
Distributed training and rollout generation often use different tensor layouts, requiring model weights to be resharded across distinct process groups. This M-to-N redistribution i…