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

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

At a recent Bengaluru mixer hosted by E2E Networks, NVIDIA, and YourStory, founders and ecosystem builders unpacked the real ...

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 ...

The key idea is that temperature differences act as inputs, and the resulting heat diffusion produces the output ...

Engineers at MIT have turned one of computing’s biggest headaches, waste heat, into the main act. By sculpting “dust-sized” silicon structures that steer heat as precisely as electrical current, they ...

Scientists in the US have created a tiny silicon chip that can perform mathematical ...

MIT researchers have designed silicon structures that can perform calculations in an electronic device using excess heat instead of electricity. These tiny structures could someday enable more ...

Abstract: Matrix multiplication is a fundamental computational operation widely used in various engineering applications. To accelerate large-scale matrix multiplication, computing tasks are commonly ...

Abstract: Sparse General Matrix-Matrix Multiplication (SpGEMM) is a core operation in high-performance computing applications such as algebraic multigrid solvers, machine learning, and graph ...

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 ...

AMD is preparing a significant redesign of its CPU architecture with the upcoming Zen 6 generation, signaling a clear break ...