Mathematicians love a good puzzle. Even something as abstract as multiplying matrices (two-dimensional tables of numbers) can feel like a game when you try to find the most efficient way to do it.

TPUs are Google’s specialized ASICs built exclusively for accelerating tensor-heavy matrix multiplication used in deep learning models. TPUs use vast parallelism and matrix multiply units (MXUs) to ...

Multiplying the content of two x-y matrices together for screen rendering and AI processing. Matrix multiplication provides a series of fast multiply and add operations in parallel, and it is built ...

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 ...

A recent paper set the fastest record for multiplying two matrices. But it also marks the end of the line for a method researchers have relied on for decades to make improvements. For computer ...

Semidynamics has announced a RISC-V Tensor Unit that is designed for ultra-fast AI solutions and is based on its fully customisable 64-bit cores. State-of-the-art Machine Learning models, such as ...