Engheta and colleagues have now set their sights on vector–matrix multiplication, which is a vital operation for the artificial neural networks used in some artificial intelligence systems. The team ...

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 ...

SparseP software package provides 25 SpMV kernels for real PIM systems supporting the four most widely used compressed matrix formats, and a wide range of data types. Our extensive evaluation provides ...

In particular, the Intel MKL DGEMM function for matrix-matrix multiplication is highly tuned for small matrices. To eliminate overhead, Intel MKL provides a compiler flag to guarantee that the fastest ...

Light accelerates the matrix multiplication for artificial intelligence Peer-Reviewed Publication. Light Publishing Center, Changchun Institute of Optics, Fine Mechanics And Physics, CAS ...

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 ...