Adjoint variational solver #3723
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Ig-dolci
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Aug 5, 2024
Ig-dolci
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Aug 6, 2024
Ig-dolci
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Ig-dolci
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Ig-dolci
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Ig-dolci
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Ig-dolci
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Sep 10, 2024
| for block_variable in self.get_dependencies(): | ||
| # The self.adj_F coefficients hold the forward output | ||
| # references. | ||
| if block_variable.output in self.adj_F.coefficients(): |
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This condition is required. We are looping over self._dependencies that are not necessarily a self.adj_F coefficient.
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This PR is linked with pyadjoint PR #172. |
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Description
This PR updates the adjoint solver by introducing a Linear Variational Solver to handle adjoint equations. It also addresses an issue arising when the Jacobian is constant and the tape recomputation is required after updating an equation parameter (a common scenario in optimisation solvers).
I have executed tests to compare computation time and memory usage between the master branch and this current branch. The tests consider three time-dependent cases:
Forward solver: Burger equation
Forward solver: Navier-Stokes equations
Forward solver: Second-order wave equation
The test scripts are available here, and the plots comparing this branch with the master branch are shown below.
Feel free to add your review to anyone interested in this PR.