Embedding CUDA Graphs in UCX for multi-path intra-node GPU communication yields up to 2.95x bandwidth improvement over single-path UCX on a four-GPU node for large messages.
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LESnets integrates LES equations and the law of the wall into F-FNO to enable data-free, stable long-term predictions of wall-bounded turbulence at Re_tau up to 1000 on coarse grids, matching traditional LES accuracy at higher efficiency.
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Accelerating Intra-Node GPU-to-GPU Communication Through Multi-Path Transfers with CUDA Graphs
Embedding CUDA Graphs in UCX for multi-path intra-node GPU communication yields up to 2.95x bandwidth improvement over single-path UCX on a four-GPU node for large messages.
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Large-eddy simulation nets (LESnets) based on physics-informed neural operator for wall-bounded turbulence
LESnets integrates LES equations and the law of the wall into F-FNO to enable data-free, stable long-term predictions of wall-bounded turbulence at Re_tau up to 1000 on coarse grids, matching traditional LES accuracy at higher efficiency.