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Characterizing GPU Effectiveness on NRP for IceCube fp32 Compute

Authors: David Schultz (University of Wisconsin, Madison); Igor Sfiligoi (University of California, San Diego (UCSD)); Benedikt Riedel (University of Wisconsin, Madison); and Frank Würthwein (University of California, San Diego (UCSD))

Abstract: The IceCube Neutrino Observatory is a cubic kilometer neutrino telescope located at the geographic South Pole. Understanding detector systematic effects is a continuous process. This requires the Monte Carlo simulation to be updated periodically to quantify potential changes and improvements in science results with more detailed modelling of the systematic effects. IceCube’s largest systematic effect comes from the optical properties of the ice the detector is embedded in. Over the last few years there have been considerable improvements in the understanding of the ice, which require a significant processing campaign to update the simulation. In winter 2023, the NRP project offered to provide the needed GPU compute to IceCube in support of this activity. Given the mostly uniform nature of such a simulation campaign, we thus have enough statistics to properly characterize the relative performance of the dozen GPU models present in the NRP in the context of IceCube.

Best Poster Finalist (BP): no

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