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

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 ...

“Several manufacturers have already started to commercialize near-bank Processing-In-Memory (PIM) architectures. Near-bank PIM architectures place simple cores close to DRAM banks and can yield ...

I'm getting ready to start working on a C/C++ project that will be building and solving large tri-diagonal, block tri-diagonal and triangular matrices. I know there are a lot of libraries available ...

This paper presents a numerical comparison between algorithms for unconstrained optimization that take account of sparsity in the second derivative matrix of the objective function. Some of the ...