Abstract: We consider a sparse matrix-matrix multiplication (SpGEMM) setting where one matrix is square and the other is tall and skinny. This special variant, TS-SpGEMM, has important applications in ...

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 ...

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

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 ...

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, ...

:param matrix_a: A square Matrix. :param matrix_b: Another square Matrix with the same dimensions as matrix_a. :return: Result of matrix_a * matrix_b. :raises ValueError: If the matrices cannot be ...

Abstract: Dense matrix-matrix multiplication algorithm is widely used in large scientific applications, and often it is an important factor of the overall performance of the application. Therefore, ...