Electrostatics simulations often employ Boundary Element Methods (BEM) that result in fully populated (dense) matrices. Direct solvers are typically used for solving of these dense linear systems. But iterative solvers can also be very effective when tunable accuracy is required. In this paper, we investigate to which extent offloading the iterative solver to a GPU accelerator can speed up the overall simulation. We use the Ginkgo library [5] as a solver backend for the Fortran-based CASOPT [17] simulations. We consider three production-relevant test cases and demonstrate the superiority of the GPU-accelerated CASOPT version.