collaborators

7 papers

cs.DC2026

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…

physics.geo-ph2026

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…

cs.DC2026

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…

cs.DC2026

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…

math.NA2026

Goal-Oriented Real-Time Bayesian Inference for Linear Autonomous Dynamical Systems With Application to Digital Twins for Tsunami Early Warning

Stefan Henneking, Sreeram Venkat, Omar Ghattas

We present a goal-oriented framework for constructing digital twins with the following properties: (1) they employ discretizations of high-fidelity PDE models governed by autonomou…

cs.DC2025

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…