6 citations · 11 across the 9 of their papers we have counts for
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Rapid Earthquake-to-Tsunami Waveform Generation via Large-Scale Multi-GPU FFT Convolution Applied to the Cascadia Subduction Zone
Bowen Shi, Sreeram Venkat, Stefan Henneking +1
Data-driven methods for earthquake and tsunami early warning rely on large ensembles of rupture scenarios and their resulting waveforms, but generating such datasets with repeated…
Accelerating High-Order Finite Element Simulations at Extreme Scale with FP64 Tensor Cores
Jiqun Tu, Ian Karlin, John Camier +4
Finite element simulations play a critical role in a wide range of applications, from automotive design to tsunami modeling and computational electromagnetics. Performing these sim…
Sensor Placement for Tsunami Early Warning via Large-Scale Bayesian Optimal Experimental Design
Sreeram Venkat, Stefan Henneking, Omar Ghattas
Real-time tsunami early warning relies on distributed sensor networks to infer seismic sources and seafloor motion. Optimizing these networks via Bayesian optimal experimental desi…
Tucker Tensor Train Taylor Series
Nick Alger, Blake Christierson, Peng Chen +1
Learning derivative-accurate surrogates for implicit simulators is a key challenge in scientific machine learning. High-order Taylor surrogates have long been considered intractabl…
Real-time probabilistic tsunami forecasting in Cascadia from sparse offshore pressure observations
Stefan Henneking, Fabian Kutschera, Sreeram Venkat +2
Near-field tsunami early warning in the Cascadia Subduction Zone is limited by sparse offshore observations. We investigate whether a hypothetical network of 175 ocean-bottom press…