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, ...

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

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 ...

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: With the advancement of Artificial Intelligence (AI), the reliability of AI accelerators has become increasingly critical. Moreover, sparse matrix multiplication has become a fundamental ...

“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 ...