9 papers
Parallel Machine Learning of Partial Differential Equations
Amin Totounferoush, Neda Ebrahimi Pour, Sabine Roller +1
In this work, we present a parallel scheme for machine learning of partial differential equations. The scheme is based on the decomposition of the training data corresponding to sp…
Resiliency in Numerical Algorithm Design for Extreme Scale Simulations
Emmanuel Agullo, Mirco Altenbernd, Hartwig Anzt +33
This work is based on the seminar titled ``Resiliency in Numerical Algorithm Design for Extreme Scale Simulations'' held March 1-6, 2020 at Schloss Dagstuhl, that was attended by a…
Multi-Node Multi-GPU Diffeomorphic Image Registration for Large-Scale Imaging Problems
Malte Brunn, Naveen Himthani, George Biros +2
We present a Gauss-Newton-Krylov solver for large deformation diffeomorphic image registration. We extend the publicly available CLAIRE library to multi-node multi-graphics process…
Fast GPU 3D Diffeomorphic Image Registration
Malte Brunn, Naveen Himthani, George Biros +2
3D image registration is one of the most fundamental and computationally expensive operations in medical image analysis. Here, we present a mixed-precision, Gauss--Newton--Krylov s…
Quasi-Newton Waveform Iteration for Partitioned Fluid-Structure Interaction
Benjamin Rüth, Benjamin Uekermann, Miriam Mehl +3
We present novel coupling schemes for partitioned multi-physics simulation that combine four important aspects for strongly coupled problems: implicit coupling per time step, fast…
Image-Driven Biophysical Tumor Growth Model Calibration
Klaudius Scheufele, Shashank Subramanian, Andreas Mang +2
We present a novel formulation for the calibration of a biophysical tumor growth model from a single-time snapshot, MRI scan of a glioblastoma patient. Tumor growth models are typi…