Scaling to the stars – a linearly scaling elliptic solver for p-multigrid

High-order methods gain increased attention in computational fluid dynamics. However, due to the time step restrictions arising from the semi-implicit time stepping for the incompressible case, the potential advantage of these methods depends critically on efficient elliptic solvers. Due to the operation counts of operators scaling with the polynomial degree p times the number of degrees of freedom nDOF, the runtime of the best available multigrid solvers scales with O(p⋅nDOF). This scaling with p significantly lowers the applicability of high-order methods to high orders. While the operators for residual evaluation can be linearized when using static condensation, Schwarz-type smoothers require their inverses on fixed subdomains. No explicit inverse is known in the condensed case and matrix-matrix multiplications scale with p⋅nDOF. This paper derives a matrix-free explicit inverse for the static condensed operator in a cuboidal, Cartesian subdomain. It scales with p3 per element, i.e. nDOF globally, and allows for a linearly scaling additive Schwarz smoother, yielding a p-multigrid cycle with an operation count of O(nDOF). The resulting solver uses fewer than four iterations for all polynomial degrees to reduce the residual by ten orders and has a runtime scaling linearly with nDOF for polynomial degrees at least up to 48. Furthermore the runtime is less than one microsecond per unknown over wide parameter ranges when using one core of a CPU, leading to time-stepping for the incompressible Navier-Stokes equations using as much time for explicitly treated convection terms as for the elliptic solvers. •Optimal complexity p-multigrid for condensed spectral elements in 3D.•Linear operation count and runtime for arbitrary ansatz order.•Exceptional convergence rates.•Computational speed comparative to fast FDM Poisson solvers.