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…
Mixed-Precision Performance Portability of FFT-Based GPU-Accelerated Algorithms for Block-Triangular Toeplitz Matrices
Sreeram Venkat, Kasia Swirydowicz, Noah Wolfe +1
The hardware diversity in leadership-class computing facilities, alongside the immense performance boosts from today's GPUs when computing in lower precision, incentivizes scientif…
Real-time Bayesian inference at extreme scale: A digital twin for tsunami early warning applied to the Cascadia subduction zone
Stefan Henneking, Sreeram Venkat, Veselin Dobrev +5
We present a Bayesian inversion-based digital twin that employs acoustic pressure data from seafloor sensors, along with 3D coupled acoustic-gravity wave equations, to infer earthq…