This project focuses on the development, optimization, and comparison of various matrix multiplication techniques for both dense and sparse matrices in high-performance environments. Matrix ...

Abstract: Artificial intelligence applications in the landing deployment, often encountered matrix multiplication and other operators in different computing platforms on the adaptation problem, need ...

The main goal of this assignment was to grasp an understanding of how divide and conquer algorithms work while experimenting with the time and space efficiency between divide & conquer, and ...

Abstract: A specialized unit in NVIDIA's GPUs, called Tensor Core, keeps attracting attention in the last couple of years due to its high computing capability for general matrix-matrix multiplications ...

DGIST announced on July 4 that Professor Min-Soo Kim's team in the Department of Information and Communication Engineering developed the DistME (Distributed Matrix Engine) technology that can analyze ...

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Can artificial intelligence (AI) create its ...

Nearly all big science, machine learning, neural network, and machine vision applications employ algorithms that involve large matrix-matrix multiplication. But multiplying large matrices pushes the ...

Alphabet Inc.’s DeepMind unit today detailed AlphaTensor, an artificial intelligence system capable of discovering new algorithms that can be used to solve mathematical problems. DeepMind researchers ...