llnl / llnl/libROM

understanding hyper-reduction in libROM

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@dylan-copeland is already working on this.

Since Mar 1, 2023.

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Description

I've been going through

https://github.com/LLNL/libROM/blob/master/examples/prom/poisson_global_rom.cpp

and it seems understandable. I want to extend it by implementing hyper-reduction.

With that in mind I'm looking at the two hyper-reduction examples

https://github.com/LLNL/libROM/blob/master/examples/prom/nonlinear_elasticity_global_rom.cpp
https://github.com/LLNL/libROM/blob/master/examples/prom/mixed_nonlinear_diffusion.cpp

And trying to correlate the description of hyper-reduction with your JCP Paper:

A fast and accurate physics-informed neural network reduced order model with shallow masked autoencoder

and your SIAM paper

SNS: A Solution-Based Nonlinear Subspace Method For Time-Dependent Model Order Reduction

Is there a better approach to understanding, and later implementing, how hyper-reduction is done in libROM?

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