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 technical paper titled “VEGETA: Vertically-Integrated Extensions for Sparse/Dense GEMM Tile Acceleration on CPUs” was published (preprint) by researchers at Georgia Tech and Intel Labs. Abstract: ...

To be more specific, a dense matrix of size N that requires N 2 storage locations in a traditional array format, while it only requires O(k/nb N 2) storage in the HiCMA H-matrix format, where k is the ...

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 ...

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