MIT researchers have designed silicon structures that can perform calculations in an electronic device using excess heat ...
A novel stacked memristor architecture performs Euclidean distance calculations directly within memory, enabling ...
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: 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 ...
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 ...
AMD researchers argue that, while algorithms like the Ozaki scheme merit investigation, they're still not ready for prime ...
Understanding the benefits of matrix converters for EV chargers and a comparison of different matrix converter topologies.
Abstract: For many scientific applications, dense matrix multiplication is one of the most important and computation intensive linear algebra operations. An efficient matrix multiplication on high ...
This repository accompanies the research paper "Implications of Language Choice for Algorithmic Efficiency in Low-Power Computing." The study investigates how the choice of programming ...