Speaker
Description
Recently, there is an increasing interest in the use of Artificial Neural Networks (ANN) in space, given the huge success of such algorithms in terrestrial applications. Industrial applications such as industrial robotics, security, unmanned autonomous vehicles and driverless cars have been driving the acceleration of such algorithms in embedded systems. In addition, even in data centres dedicated hardware accelerators have been successfully deployed and shown to have a large increase in power efficiency over traditional software approaches.
At ESA there are currently several on-going activities aimed at enabling new highly processing intensive applications, such as ANN based deep learning image processing, in embedded systems for space.
This short paper outlines the on-going activities at ESA for high performance processing systems and how they can be applied on deep learning applications. It also gives an overview of available commercial technologies for ANN acceleration such as dedicated integrated circuits, embedded processors and FPGA. Currently available radiation hardened devices are also analysed for their suitability.
Summary
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| Paper submission | Yes |
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