Photonics is promising to handle extensive vector multiplications in AI applications. Scientists in China have promoted a programmable and reconfigurable photonic linear vector machine named SUANPAN, ...

A new technique from Stanford, Nvidia, and Together AI lets models learn during inference rather than relying on static ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...

Abstract: Matrix-vector multiplication is practically used in all Digital Signal Processing (DSP) algorithms. Particularly, in the channel emulation field, it is required to perform this algorithm in ...

Abstract: We propose COSMA: a parallel matrix-matrix multiplication algorithm that is near communication-optimal for all combinations of matrix dimensions, processor counts, and memory sizes. The key ...

Researchers at Massachusetts Institute of Technology have demonstrated a surprising new way to compute—by using heat instead ...

A team of researchers developed “parallel optical matrix-matrix multiplication” (POMMM), which could revolutionize tensor ...

A research team has successfully implemented a programmable spinor lattice on a photonic integrated circuit (PIC). This platform enables the realization of non-Abelian physics, in which the outcome of ...

Weijia Shang received BS degree in computer engineering from Changsha Institute of Technology, China, and Master and Ph.D. degrees in computer engineering from Purdue University, West Lafayette, ...

This repository contains the artifact for the SC '25 paper submission "KAMI: Communication-Avoiding General Matrix Multiplication within a Single GPU." The NVIDIA GH200 is installed with Ubuntu 22.04 ...

TTT-Discover performs reinforcement learning at test time, allowing the LLM to continue training with experience specific to the problem at hand. We achieve new state-of-the-art across mathematics, ...