Abstract: In this study, physics-informed graph residual learning (PhiGRL) is proposed as an effective and robust deep learning (DL)-based approach for 3-D electromagnetic (EM) modeling. Extended from ...
Abstract: Determining optimal CUDA block size configurations represents a critical challenge in GPU-based graph processing. The block size directly impacts execution efficiency by balancing kernel ...
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