TPUs are Google’s specialized ASICs built exclusively for accelerating tensor-heavy matrix multiplication used in deep learning models. TPUs use vast parallelism and matrix multiply units (MXUs) to ...

Researchers at FOM Institute for Atomic and Molecular Physics (AMOLF) in the Netherlands have developed a new type of soft, flexible material that can perform complex calculations, much like computers ...

Abstract: We demonstrate an optical general matrix multiplication using incoherent light source and wavelength multiplexing to multiply two two-dimensional matrices with positive and negative elements ...

Dozens of machine learning algorithms require computing the inverse of a matrix. Computing a matrix inverse is conceptually easy, but implementation is one of the most challenging tasks in numerical ...

Discovering faster algorithms for matrix multiplication remains a key pursuit in computer science and numerical linear algebra. Since the pioneering contributions of Strassen and Winograd in the late ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of computing a matrix inverse using the Newton iteration algorithm. Compared to other algorithms, Newton ...

Meta is now using the Threads.com domain name for its X competitor Threads. Credit: Arda Kucukkaya/Anadolu Agency via Getty Images Threads, Meta's alternative to X, formerly Twitter, had almost ...

The Nature Index 2025 Research Leaders — previously known as Annual Tables — reveal the leading institutions and countries/territories in the natural and health sciences, according to their output in ...

This project implements a matrix multiplication system using POSIX threads in C. The program offers both single-threaded and multi-threaded approaches to matrix multiplication, allowing users to ...

An NPU is a dedicated hardware accelerator designed to perform AI operations much more efficiently and faster than CPUs and GPUs. NPU cores are specifically designed to perform matrix multiplication ...