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Author

Xipeng Shen

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Preprint Sep 2026

Scaling Fourier-Based Sparse Matrix Analysis on GPUs

Sparse computations are important workloads in applications such as scientific computing, graph neural networks (GNNs), and machine learning. While many sparse operations can benefit from modern GPUs, the sparsity pattern remains important to performance because it affects memory coalescing, block organization, and loa...

Rui-Feng Zhang, Sai Akhil Varma Manthena, Jia-Jia Li et al. · 0 citations
#machine learning Preprint Aug 2026

Spectral Analysis for Sparse Matrix Computation: Insights and Potential

This work gives the first known exploration of the connections between sparse matrix computation and spectral analysis by treating sparse matrices as two-dimensional signals and analyzing their frequency-domain representations through Fast Fourier Transform.

Rui-Feng Zhang, Xi-Peng Shen · 1 citation

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