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: In modern machine learning models like Transformers, matrix multiplication dominates most computation. Specific hardware often uses large-scale PE arrays, such as systolic arrays, to ...
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