Abstract: Achieving high performance for Sparse Matrix-Matrix Multiplication (SpMM) has received increasing research attention, especially on multi-core CPUs, due to the large input data size in ...

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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 ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Implementations of matrix multiplication via diffusion and reactions, thus eliminating ...

Discovering faster algorithms for matrix multiplication remains a key pursuit in computer science and numerical linear algebra. Since the pioneering contributions of Strassen and Winograd in the late ...

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 ...

In this assignment, you'll be investigating the performance impacts of different cache architectures and different algorithm designs on matrix multiplication. The goals of this assignment are: Show ...

A new technology for autonomously operating aircraft dubbed "MATRIX" is drawing scrutiny across social media after a commercial airliner collided with a military helicopter in Washington, D.C. on ...

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 ...