17-19 March 2020
European Space Research and Technology Centre (ESTEC)
Europe/Amsterdam timezone
UPDATE 02 March 2020: please be informed that SEFUW has been postponed. More information will be posted here in due course.

Xilinx Machine Learning Solutions and Design Considerations for Space Applications

19 Mar 2020, 11:20
Newton 1 and 2 (European Space Research and Technology Centre (ESTEC))

Newton 1 and 2

European Space Research and Technology Centre (ESTEC)

Keplerlaan 1 2201AZ Noordwijk ZH The Netherlands
Artificial Intelligence/Machine Learning Artificial Intelligence/Machine Learning


Mr Jason Vidmar (Xilinx Corp)


In the past decade, the field of Machine Learning has witnessed dramatic breakthroughs in the state of the art for tasks such as image classification and object detection, aided by advancements in algorithms, training data and computing architectures. To date, most results have been demonstrated for terrestrial applications, but there is significant demand for solutions that can scale these capabilities into the Space environment, where on-board Machine Learning combined with high performance sensor packages could offer a dramatic reduction in decision latency. In this session, we will discuss Xilinx hardware and software solutions suitable for enabling high performance, low-latency, SWaP-optimized machine learning acceleration for Space applications; as well as the associated design requirements. Solution types covered include the Xilinx Deep Learning Processor Unit, as well as third-party and fabric-based options.

Primary author

Mr Jason Vidmar (Xilinx Corp)


Ms Minal Sawant (Xilinx)

Presentation Materials

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