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What is On the Horizon for Processing Units in 2020?

The Possibility of Photon-based Tensor Processing Units Mid-2020

What is on the horizon for processing units? You might have heard of CPU, maybe GPU or even TPU. I saw an article about the development of a new Tensor Processing Unit (TPU), and that it provided for an interesting possibility. Namely that of photon-based tensor processing units.

TPU is an acronym for Tensor Processing Unit. According to Wikipedia the definition is the following:

I have written more of these previously.

This June in 2020 there is a paper that proposes a new approach to performing computations.

It proposes to use light instead of electricity to perform these computations required by a neural network.

Within this — a photonic tensor core performs multiplications of matrices in parallel.

Thus, it is said, improving speed and efficiency of current deep learning paradigms.

There is an article discussing this research in .

In some machine learning techniques neural networks are trained to perform unsupervised decision and classification on data that has not been seen.

Trained on data → to make an inference → recognise and or classify objects.

This is of course a gross simplification of a complex process that does not necessarily happen in this sequences or specific manner.

One attempts to find a signature or pattern in the data.

Photonic TPU is said to store data in parallel featuring an electro-optical interconnect. This supposedly allow the optical memory to be efficiently read and written, and the photonic TPU to

These consume a fraction of power and have higher throughput.

There are multiple layers of interconnected ‘neurons’ in some of the neural networks.

These networks can become incredible complex.

They demand vast amounts of data for computation, and power to process the data.

and are limited by the transmission of electronic data between the processor and the memory.

The researchers showed that the performance of their TPU could be than an electrical TPU.

The article in ScienceDaily argues that it could be of interest in :

If this is done then there is a possibility to reduce data centre traffic in certain processing tasks.

Data processed faster, due to preprocessed data, meaning only a portion of the data needs to be sent to the cloud or data centre.

One the one hand this is of course highly possible, yet on the other hand it is still in the research phase so we must show some patient and think of this with some moderation.

AI Policy and Ethics at www.nora.ai. Student at University of Copenhagen MSc in Social Data Science. All views are my own. twitter.com/AlexMoltzau