The evidence is solid but not definitive, as the conclusions rely on the absence of changes in spatial breadth and would benefit from clearer statistical justification and a more cautious ...

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: The design of sparse synthesis has been paying much attention in recent years due to the control of system cost. Concurrently, phase quantization is increasingly being considered for system ...