Solving many scientific and technical applications entails the use of matrix multiplies somewhere in the algorithm and thus the computer code. With today’s multicore CPUs, proper use of complier ...

A recent paper set the fastest record for multiplying two matrices. But it also marks the end of the line for a method researchers have relied on for decades to make improvements. For computer ...

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 ...

Computer scientists have discovered a new way to multiply large matrices faster than ever before by eliminating a previously unknown inefficiency, reports Quanta Magazine. This could eventually ...

Inverting a matrix is one of the most common tasks in data science and machine learning. In this article I explain why inverting a matrix is very difficult and present code that you can use as-is, or ...

Most traditional high-performance computing applications focus on computations on very large matrices. Think seismic analysis, weather prediction, structural analysis. But today, with advances in deep ...