Primary Algorithm : Algorithmically, Sparse-Sparse multiplication problems manifests itself in three possible forms:(a) Multiplication of a sparse matrix with a sparse diagonal, sparse block-diagonal, ...

This project is a hardware matrix multiplication accelerator that computes C = A × B for N×N matrices (currently only tested for NxN matrices, however the design is parameterized and with small ...

Abstract: The rising popularity of deep learning algorithms demands special accelerators for matrix-matrix multiplication. Most of the matrix multipliers are designed based on the systolic array ...

In this video from PASC17, Alfio Lazzaro (University of Zurich, Switzerland) presents: Increasing Efficiency of Sparse Matrix-Matrix Multiplication. “Matrix-matrix multiplication is a basic operation ...

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

Abstract: Distributed computations, such as distributed matrix multiplication, can be vulnerable to significant security issues, notably Byzantine attacks. These attacks may target either worker nodes ...

Sparse matrix computations are prevalent in many scientific and technical applications. In many simulation applications, the solving of the sparse matrix-vector multiplication (SpMV) is critical for ...

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 ...