[solver]: Solver for large linear systems.

[epprob]

Use an iterative or conjugate gradient solver for both blood flow and adjoint equations. Currently, the direct solver requires 96% of run time while solving an inverse problem with 100'000 vertices

[epprob]

Maybe, @clambr when you have done the implementation of the iterative solver, you could post a comparison of the run time of both solvers here (screenshot of profiling, as I did above).

[clambr]

For an iterative solver, I used the PyAMG, a library of Algebraic Multigrid (AMG) solvers. from pyamg import smoothed_aggregation_solver from scipy.sparse.linalg import cg

testcase_inverse_problem.py

for max_nr_of_iterations = 5

Direct Solver

Iterative Solver