Engheta and colleagues have now set their sights on vector–matrix multiplication, which is a vital operation for the artificial neural networks used in some artificial intelligence systems. The team ...

Photonic accelerators have been widely designed to accelerate some specific categories of computing in the optical domain, especially matrix multiplication, to address the growing demand for ...

However, it was designed for complex-valued matrix-vector multiplication, a type of computation that has hardware requirements different from those of real-valued matrix-vector multiplication.

In DeepMind’s new algorithm, dubbed AlphaTensor, the inputs represent steps along the way to a valid matrix multiplication scheme. The first input to the neural network is the original matrix ...

Modern artificial intelligence systems rely on deep neural networks (DNNs) that demand immense computational resources. Traditional electronic processors often struggle to meet the growing needs ...

"Matrix multiplication is the most prevalent calculation in neural networks for artificial intelligence," said Woo-Bin Jung, a postdoctoral fellow at SEAS and the first author of the paper.

Prof. Kim says, "In this study, we achieved SC on a high-density two-terminal memristor and implemented vector-matrix multiplication (VMM), the core of AI semiconductor computation, on a 32 x 32 ...

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 ...