Multigrid In Energy Preconditioner for Krylov Solvers
This work addresses the need for scalable preconditioners in radiation transport simulations, improving solver efficiency for high-performance computing.
The authors developed a multigrid in energy (MGE) preconditioner for the Denovo radiation transport code, which reduces Krylov iterations by leveraging a multilevel energy decomposition, enabling efficient scaling to hundreds of thousands of cores.
We have added a new multigrid in energy (MGE) preconditioner to the Denovo discrete-ordinates radiation transport code. This preconditioner takes advantage of a new multilevel parallel decomposition. A multigroup Krylov subspace iterative solver that is decomposed in energy as well as space-angle forms the backbone of the transport solves in Denovo. The space-angle-energy decomposition facilitates scaling to hundreds of thousands of cores. The multigrid in energy preconditioner scales well in the energy dimension and significantly reduces the number of Krylov iterations required for convergence. This preconditioner is well-suited for use with advanced eigenvalue solvers such as Rayleigh Quotient Iteration and Arnoldi.