GitHub

A Python demonstration of speeding up matrix multiplication and reducing memory using a quantum-inspired low-rank SVD trick, with examples in AI.

This repository demonstrates a powerful, classical linear algebra technique—low-rank approximation via Singular Value Decomposition (SVD)—to dramatically accelerate common matrix operations like GEMM ...
GitHub

ranimeshehata/Sparse-Matrix-Vector-Multiplication

A high-performance implementation of Sparse Matrix-Vector Multiplication in C++ with serial, parallel (OpenMP), and GPU-accelerated (CUDA) versions, demonstrating the performance benefits of ...
IEEE

Performance Analysis of the Parallel Shared-Memory Sparse Matrix-Vector Multiplication on Unstructured Matrices

Abstract: This paper investigates sparse matrix-vector (SpMV) multiplication algorithm performance for unstructured sparse matrices. The development of an SpMV multiplication algorithm for this type ...
Physics World

Photonic metastructure does vector–matrix multiplication

Photonic innovation: researchers in the US have created an optical metamaterial that can perform vector–matrix multiplication. (Courtesy: iStock/Henrik5000) A new silicon photonics platform that can ...
Semiconductor Engineering

SparseP: Towards Efficient Sparse Matrix Vector Multiplication on Real Processing-In-Memory Systems

“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 ...