A strip of wood unearthed during 2001 excavations at the site of the ancient Japanese capital city of Fujiwara-kyo is a far more sophisticated artifact than it appears at first glance. After more than ...

Abstract: Deep neural networks (DNNs) have been widely applied in our society, yet reducing power consumption due to large-scale matrix computations remains a critical challenge. MADDNESS is a known ...

Multiplication in Python may seem simple at first—just use the * operator—but it actually covers far more than just numbers. You can use * to multiply integers and floats, repeat strings and lists, or ...

Assemblyman Jeffrey Dinowitz, D-Bronx, speaks on the Assembly floor in March. It’s been a while since some school districts have used old-school multiplication tables. Assemblyman Jeffrey Dinowitz, ...

A young computer scientist and two colleagues show that searches within data structures called hash tables can be much faster than previously deemed possible. Sometime in the fall of 2021, Andrew ...

Discover how nvmath-python leverages NVIDIA CUDA-X math libraries for high-performance matrix operations, optimizing deep learning tasks with epilog fusion, as detailed by Szymon Karpiński.

Abstract: Multiplying matrices is among the most fundamental and compute-intensive operations in machine learning. Approximated Matrix Multiplication (AMM) based on table look-ups can significantly ...

Benjamin holds a Master's degree in anthropology from University College London and has previously worked in the fields of psychedelic neuroscience and mental health. Benjamin holds a Master's degree ...