This project demonstrates matrix multiplication using the Hadoop MapReduce framework. It explains how large matrix computations can be performed efficiently in a distributed environment using Hadoop.

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 ...

Optical computing uses photons instead of electrons to perform computations, which can significantly increase the speed and energy efficiency of computations by overcoming the inherent limitations of ...

Abstract: Sparse matrix-vector multiplication (SpMV) is a critical kernel in scientific computing and high-performance applications, yet it remains challenging to optimize due to irregular memory ...

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 ...

“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 ...