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

Researchers at MIT's Computer Science & Artificial Intelligence Lab (CSAIL) have open-sourced Multiply-ADDitioN-lESS (MADDNESS), an algorithm that speeds up machine learning using approximate matrix m ...

Tensor for matrix multiplication and algorithms: here multiplication of 2 x 2 matrices. Entries equal to 1 are purple, 0 entries are semi-transparent.

According to Google DeepMind, AlphaEvolve has successfully discovered multiple new algorithms for matrix multiplication, surpassing the previous AlphaTensor model in efficiency and performance (source ...

The algorithm has stood as the most efficient approach on most matrix sizes for more than 50 years, although some slight improvements that aren’t easily adapted to computer code have been found.

The algorithm is able to re-discover older matrix multiplication algorithms and improve upon its own to discover newer and faster algorithms. “AlphaTensor is the first AI system for discovering novel, ...

Since Volker Strassen proposed a recursive matrix multiplication algorithm reducing the time complexity to n2.81 in 1968, many scholars have done a lot of research on this basis. In recent years, ...