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Boffins from the Delft University of Technology (TU Delft) and European Space Agency (ESA) have penned a paper detailing the design of a processor they hope could run deep neural networks in space – building on the free and open-source RISC-V architecture and its vector extensions.

“One of the main issues in terms of hardware faced by the space industry is that it is not possible to reuse in a straightforward way the hardware platforms employed in terrestrial applications,” the researchers explained, “given the specific constraints of satellite data systems especially in terms of robustness to ionising radiation.”

By way of example the team cited a 2019 paper [PDF] in which an off-the-shelf AMD graphics processor of the type commonly used to accelerate machine learning workloads was placed in the path of a proton beam to simulate radiation exposure in space – and proceeded to fail every 43 seconds, give or take.

Couple that with high-performance processors being typically energy-hungry too and the dream of running deep neural networks in space seems to be just that – a dream.

Read the full article here.

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