Abstract
Structured sparse matrices are common in various fields of knowledge, from neural network acceleration and compression to numerical solutions of partial differential equations. The vast majority of applications that use sparse matrices in their operations (e.g., neural networks) involve large volumes of data, which result in long computation times. Although there are algorithms for sparse…