Novel Solver Algorithms for Nearly Singular Linear Systems Arising in Combustion Modelling

Paul Mullowney, Stephen Thomas, Arielle Carr, Katarzyna Swirydowicz, Marcus Day, Lucas Esclapez

Research output: NRELPresentation


Direct Numerical Simulations of realistic combustion devices are extremely challenging due to the wide separation of scales in the simulation, for example an internal combustion (IC) engine chamber, and the flame thickness of a high-pressure flame. The PeleLMeX solver uses adaptive mesh refinement (AMR) to evolve multi-species reacting flows in the low Mach number limit at the Exascale and relies on an embedded boundary (EB) approach to represent complex geometries. In that framework, the EB geometries often give rise to very small cut-cells along the boundary, which translate into extreme ill-conditioning of the pressure-projection, with eigenvalues that span 15-16 orders of magnitude. In this talk, we focus on the case of a typical IC piston bowl geometry for which we present on a novel approach towards solving these nearly singular linear systems with ILU-based, C-AMG smoothers on massively parallel architectures. In particular, we use scaling and equilibration algorithms to handle the non-normality of the upper triangular factors. This enables us to approximate the highly sequential triangular solve algorithm, embedded in the AMG smoothing-solve phase, with Jacobi iterations. This approximation can be written as a convergent Neumann series whose terms are composed of highly parallel sparse matrix vector multiplications. The result is an algorithm that substantially decreases setup and solve time, compared to state-of-the-art, for these challenging linear systems.
Original languageAmerican English
Number of pages20
StatePublished - 2022

Publication series

NamePresented at the SIAM Conference on Parallel Processing for Scientific Computing, 23-26 February 2022

NREL Publication Number

  • NREL/PR-2C00-81907


  • combustion modelling
  • computational linear algebra
  • exascale computing
  • GPU computing


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