Tech Xplore on MSN
Tiny silicon structures compute with heat, achieving 99% accurate matrix multiplication
MIT researchers have designed silicon structures that can perform calculations in an electronic device using excess heat ...
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 ...
Morning Overview on MSN
MIT’s heat-powered silicon chips hit 99% accuracy in math tests
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 ...
A novel stacked memristor architecture performs Euclidean distance calculations directly within memory, enabling ...
Numerical computation and mathematical software form the backbone of modern scientific inquiry, facilitating the approximation of real numbers, the solution of complex mathematical models, and the ...
Researchers at Massachusetts Institute of Technology have demonstrated a surprising new way to compute—by using heat instead of electricity. In a proof-of-concept study published in Physical Review ...
Abstract: Under the nearing error-corrected era of quantum computing, it is necessary to understand the suitability of certain post-NISQ algorithms for practical problems. One of the most promising, ...
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 ...
Abstract: Numerous studies have proposed hardware architectures to accelerate sparse matrix multiplication, but these approaches often incur substantial area and power overhead, significantly ...
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