Multiplication in Python may seem simple at first—just use the * operator—but it actually covers far more than just numbers. You can use * to multiply integers and floats, repeat strings and lists, or ...

Dozens of machine learning algorithms require computing the inverse of a matrix. Computing a matrix inverse is conceptually easy, but implementation is one of the most challenging tasks in numerical ...

Either way, let’s not be in denial about it. Credit...Illustration by Christoph Niemann Supported by By Kevin Roose and Casey Newton Kevin Roose and Casey Newton are the hosts of The Times’s “Hard ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of computing a matrix inverse using the Newton iteration algorithm. Compared to other algorithms, Newton ...

Abstract: This paper investigates the impact of loop unrolling on CUDA matrix multiplication operations’ performance across NVIDIA GPUs. We benchmarked both basic and unrolled kernels with varying ...

A reinforcing loop is one type of causal loop, a term used to describe one way a number of variables can be connected. In a reinforcing loop specifically, one variable reinforces another, which in ...

Abstract: We consider how to map sparse matrices across processes to reduce communication costs in parallel sparse matrix-vector multiplication, an ubiquitous kernel in high performance computing. Our ...

Researchers claim to have developed a new way to run AI language models more efficiently by eliminating matrix multiplication from the process. This fundamentally redesigns neural network operations ...