Author

Pouya Kousha

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Preprint Oct 2026

NCCL M2N: A Layout- and Topology-Aware Collective for Distributed Tensor Resharding

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 is not directly expressed by standard collectives. Flat direct sends duplicate traffic across destination replicas, while gather-then-broadca...

Kaushik Kandadi, Youngeun Kwon, S. Potluri et al. · 0 citations

Jul 2026

Every Microsecond Matters: Achieving Near Speed-of-Light Latency in GPU Collectives

Building on NCCL's device-side API, low-latency interfaces for constructing custom collective kernels are developed and used to implement new symmetric collectives in NCCL, demonstrating benefits for both AI inference and traditional HPC workloads.

Siyuan Shen, Anton Korzh, J. Bachan et al. · arXiv.org · 0 citations