Hello, We have a specific question about how a solver helps in accelerating convergence of a loosely coupled system of PDEs.
Due to the fundamentally different properties/behaviour/geometry, we have a loosely coupled system of 8 PDEs defined along 5 different meshes, with data manually copied from certain regions of one mesh to suitable regions of another after sweeping each PDE. Quite unsurprisingly, the system of equations needs a lot of sweeps (80 to 100) within each time-step to converge, and consequently the simulation model isn't useable. Although, the trilinos based parallel solvers are correctly set-up and working correctly for the example problems shipped with FiPy, the mpirun command complains when invoked on our (complicated script). We assume that it is due to the complicated setup of meshes and the classes/methods and objects that we have instantiated for our application. The serial code runs just fine. So, in order to speed up our simulation, we looked to implement dynamic relaxation factors for the sweeps. This has only a limited success so far. Next, I wonder whether including a Successive over-relaxation solver will help in this case ? There are 8 PDEs to be swept continuously until the residue of all of them gets lowered below a tolerance. Does the Fipy's JOR solver (wrapper for Pysparse Jacobi/over-relaxation solvers) help in this case ? is there any other way to speed up our system ? Best Regards Krishna
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