Sparse matrix-matrix multiplication (SpMM) is a crucial kernel in various applications, including sparse deep neural networks [1]–[6], graph analytics [7], triangle counting [8], and linear algebra ...
Abstract: Efficient representation of sparse matrices is critical for reducing memory usage and improving performance in hardware-accelerated computing systems. This letter presents memory-efficient ...
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