Abstract: Numerous studies have proposed hardware architectures to accelerate sparse matrix multiplication, but these approaches often incur substantial area and power overhead, significantly ...

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Abstract: Graph convolutional networks (GCNs) are emerging neural network models designed to process graph-structured data. Due to massively parallel computations using irregular data structures by ...