A scalable preconditioner for a DPG method
This work provides a practical preconditioner for large-scale DPG simulations, addressing a key bottleneck in computational mechanics.
The authors developed a scalable algebraic multigrid preconditioner for the DPG method, achieving the first massively scalable algebraic preconditioner for such problems.
We show how a scalable preconditioner for the primal discontinuous Petrov-Galerkin (DPG) method can be developed using existing algebraic multigrid (AMG) preconditioning techniques. The stability of the DPG method gives a norm equivalence which allows us to exploit existing AMG algorithms and software. We show how these algebraic preconditioners can be applied directly to a Schur complement system of interface unknowns arising from the DPG method. To the best of our knowledge, this is the first massively scalable algebraic preconditioner for DPG problems.