Abstract: Efficiently synthesizing an entire application that consists of multiple algorithms for hardware implementation is a very difficult and unsolved problem. One of the main challenges is the ...

Sparse matrix-matrix multiplication (SpMM) is a crucial kernel in various applications, including sparse deep neural networks [1]–[6], graph analytics [7], triangle counting [8], and linear algebra ...

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 ...

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 ...

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 report didn’t specify the valuation that FuriosaAI is expected to receive. The company was worth $735 million as of July, ...

New silicon designs apply AI to processing and enhancing digital audio. Cadence has new IP to simplify the work.

AMD researchers argue that, while algorithms like the Ozaki scheme merit investigation, they're still not ready for prime ...

By moving model runs to iPhones and Macs, Apple cuts reliance on data centers and lowers energy use, so you get quicker, ...

Python turns 32. Explore 32 practical Python one-liners that show why readability, simplicity, and power still define the ...

While Apple and Nvidia are both huge tech companies, Apple designs its own chips for its devices like iPhones and Macs. They ...