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MatrixFSDP: communication-free matrix optimizers under ZeRO-3 parameter sharding
Matrix optimizers such as Muon are attractive for large-scale training because they can improve convergence and token efficiency over coordinate-wise optimizers. Muon does this by orthogonalizing momentum-smoothed matrix updates with Newton-Schulz, producing spectrum-balanced updates that require th
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