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 ...

Abstract: While the Karatsuba algorithm reduces the complexity of large integer multiplication, the extra additions required minimize its benefits for smaller integers of more commonly-used bitwidths.

Take your coding to the next level by learning advanced programming with generics. Here's how to use generic methods with type inference, type parameters, and wildcards in your Java programs. Generics ...

As artificial intelligence continues to reshape the tech landscape, developers are increasingly faced with the task of selecting which programming languages are the most beneficial and effective in ...

ParserNG is a powerful , fast math expression parser that parses and evaluates math expressions, does differential calculus(symbolic) evaluations, numerical ...

A team of software engineers at the University of California, working with one colleague from Soochow University and another from LuxiTec, has developed a way to run AI language models without using ...

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 ...

Presenting an algorithm that solves linear systems with sparse coefficient matrices asymptotically faster than matrix multiplication for any ω > 2. Our algorithm can be viewed as an efficient, ...

Matrix multiplication (MatMul) is a fundamental operation in most neural networks, primarily because GPUs are highly optimized for these computations. Despite its critical role in deep learning, ...