Abstract: We propose an efficient quantum subroutine for matrix multiplication that computes a state vector encoding the entries of the product of two matrices in superposition. The subroutine ...

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 ...

The program uses basic Python programming concepts to perform matrix operations without any built-in libraries. Matrices are stored using nested lists where each inner list represents one row of the ...

This repository contains a comprehensive collection of Verilog HDL implementations of fundamental and advanced digital design components. These designs include arithmetic circuits, memory elements, ...