Familiarity with linear algebra is expected. In addition, students should have taken a proof-based course such as CS 212 or Math 300. Tensors, or multiindexed arrays, generalize matrices (two ...

Algorithms have been used throughout the world’s civilizations to perform fundamental operations for thousands of years. However, discovering algorithms is highly challenging. Matrix multiplication is ...

The cover shows an artistic impression of a matrix multiplication tensor — a 3D array of numbers — in the process of being solved by deep learning. Efficient matrix multiplication algorithms can help ...

A custom-built AI chip from Google. Introduced in 2016 and used in Google Cloud datacenters, the Tensor Processing Unit (TPU) is designed for matrix multiplication, which is the type of processing ...

Researchers have created a new system that automatically produces code optimized for sparse data. We live in the age of big data, but most of that data is "sparse." Imagine, for instance, a massive ...

New Linear-complexity Multiplication (L-Mul) algorithm claims it can reduce energy costs by 95% for element-wise tensor multiplications and 80% for dot products in large language models. It maintains ...

Researchers in China published a paper describing a theoretical model for photonic computing that used light particles instead of electrons for faster processing. The team developed “parallel optical ...