Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of computing a matrix inverse using ...

High-performance matrix multiplication remains a cornerstone of numerical computing, underpinning a wide array of applications from scientific simulations to machine learning. Researchers ...

Prasun Chaudhuri speaks to expert Subrata Das about the opportunities. Das is currently an adjunct faculty member at ...

In this paper, we propose a scheme for matrix-matrix multiplication on a distributed-memory parallel computer. The scheme hides almost all of the communication cost with the computation and uses the ...

Nvidia is in outstanding financial health. As of April 2025, the company held $53.7 billion in cash and investments, as compared with $8.5 billion in short-term and long-term debt.

AI algorithms using neural networks can estimate object positions from complex optical patterns with precision approaching the theoretical limit set by the Fisher information.

Researchers have developed algorithms that reconstruct a hidden image from the scrambled light waves that bounce off a wall, making it possible to see things behind a corner ...

If your algorithm solves a real problem in a non-obvious way, it’s worth exploring protection. If you can describe its technical function and improvements clearly, it may qualify.

Matrix multiplication is an important topic of linear algebra and is something that is not intuitive as you might think. When you think about multiplication and matrix, the thing that comes to your ...