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DOE OSTI · 2371660

An Intermediate Level Trigger Supernova Pointing Trigger for DUNE Using In-Storage AI

Wang, Michael H.L.S.
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Abstract

We propose a near-data approach to reduce the buffered supernova data on the DUNE DAQ front-end computers using ML techniques. Based on simulations, we are able to reduce the data by 5 orders of magnitude to 0(100)MB which can then be transferred quickly over ethernet to a single server that executes a full reconstruction and pointing analysis to determine the SN direction. The entire process of reducing the data and executing reconstruction and pointing analysis pipeline takes less time than that required to transfer all the data back to Fermilab before performing more processing to determine the direction of the supernova, which was the baseline plan for DUNE.

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BibTeXRIS

Wang, Michael H.L.S.. 2024-04-22. An Intermediate Level Trigger Supernova Pointing Trigger for DUNE Using In-Storage AI. https://doi.org/10.2172/2371660

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