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HyperParallel-FSDP: Topology-Aware Fully Sharded Training with Layout-Driven Muon on Ascend SuperPods
Declarative SPMD programming uses tensor sharding descriptions to drive distributed execution, separating parallelization from model code. However, the evaluated PyTorch DTensor stack dispatches every operator below autograd, incurring repeated dispatch and metadata costs, while lacking an inexpensi
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