Sparse matrix computations are pivotal to advancing high-performance scientific applications, particularly as modern numerical simulations and data analyses demand efficient management of large, ...

A novel AI-acceleration paper presents a method to optimize sparse matrix multiplication for machine learning models, particularly focusing on structured sparsity. Structured sparsity involves a ...

This approach enables block encoding of any sparse matrix with a clear gate-level construction, significantly reducing circuit complexity and control overhead, bringing quantum algorithms closer to ...