A new research paper titled “Discovering faster matrix multiplication algorithms with reinforcement learning” was published by researchers at DeepMind. “Here we report a deep reinforcement learning ...

With AlphaTensor, DeepMind Technologies has presented an AI system that is supposed to independently find novel, efficient and provably correct algorithms for complex mathematical tasks. AlphaTensor ...

AlphaTensor, builds upon AlphaZero, an agent that has shown superhuman performance on board games, like chess, Go and shogi, and this work shows the journey of AlphaZero from playing games to tackling ...

High-performance matrix multiplication remains a cornerstone of numerical computing, underpinning a wide array of applications from scientific simulations to machine learning. Researchers continually ...

What do encrypted messages, recognizing speech commands and running simulations to predict the weather have in common? They all rely on matrix multiplication for accurate calculations. DeepMind, an ...

Abstract: Summary form only given. We describe a novel parallel algorithm that implements a dense matrix multiplication operation with algorithmic efficiency equivalent to that of Cannon's algorithm.

This repository explores the performance and implementation of various matrix multiplication algorithms. The primary goal was to benchmark a range of algorithms, from the classic textbook method to ...

This work focuses on the study of state-of-practice distributed algorithms for general matrix multiplication and their shortcomings when executed in modern multi-node multi-GPU systems. By utilizing ...