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.

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 ...

Nearly all big science, machine learning, neural network, and machine vision applications employ algorithms that involve large matrix-matrix multiplication. But multiplying large matrices pushes the ...

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 ...

Researchers at MIT's Computer Science & Artificial Intelligence Lab (CSAIL) have open-sourced Multiply-ADDitioN-lESS (MADDNESS), an algorithm that speeds up machine learning using approximate matrix ...

“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 ...