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 ...
High-performance matrix multiplication remains a cornerstone of numerical computing, underpinning a wide array of applications from scientific simulations to machine learning. Researchers continually ...
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 ...
Abstract: The paper presents a novel methodology to implement resource efficient 64-bit floating point matrix multiplication algorithm using FPGA. Approach uses systolic architecture using four ...
Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. This article dives into the happens-before ...
The 'algorithm for calculating the matrix product' that AlphaTensor worked on this time is used in various fields related to daily life, such as image processing, game graphics processing, weather ...
This project demonstrates the use of the MapReduce framework to solve the matrix multiplication problem. Matrix multiplication is a common computational task in fields like scientific computing, ...
Rice University computer scientists have overcome a major obstacle in the burgeoning artificial intelligence industry by showing it is possible to speed up deep learning technology without specialized ...
Introduction to 2D Arrays (Multidimensional Arrays) A 2D array is an array of arrays, often used to represent matrices or tables with rows and columns. It stores data in a grid-like structure, where ...
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