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.

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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 ...

A processing unit in an NVIDIA GPU that accelerates AI neural network processing and high-performance computing (HPC). There are typically from 300 to 600 Tensor cores in a GPU, and they compute ...

Over at the NVIDIA blog, Loyd Case shares some recent advancements that deliver dramatic performance gains on GPUs to the AI community. We have achieved record-setting ResNet-50 performance for a ...

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 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 ...