Symbolic construction of the chemical Jacobian of quasi-steady state (QSS) chemistries for Exascale computing platforms
<|reference_start|>Symbolic construction of the chemical Jacobian of quasi-steady state (QSS) chemistries for Exascale computing platforms: The Quasi-Steady State Approximation (QSSA) can be an effective tool for reducing the size and stiffness of chemical mechanisms for implementation in computational reacting flow solvers. However, for many applications, stiffness remains, and the resulting model requires implicit methods for efficient time integration. In this paper, we outline an approach to formulating the QSSA reduction that is coupled with a strategy to generate C++ source code to evaluate the net species production rate, and the chemical Jacobian. The code-generation component employs a symbolic approach enabling a simple and effective strategy to analytically compute the chemical Jacobian. For computational tractability, the symbolic approach needs to be paired with common subexpression elimination which can negatively affect memory usage. Several solutions are outlined and successfully tested on a 3D multipulse ignition problem, thus allowing portable application across a chemical model sizes and GPU capabilities. The implementation of the proposed method is available at https://github.com/AMReX-Combustion/PelePhysics under an open-source license.<|reference_end|>
@article{hassanaly2024symbolic,
    title={Symbolic construction of the chemical Jacobian of quasi-steady state
  (QSS) chemistries for Exascale computing platforms},
    author={Malik Hassanaly, Nicholas T. Wimer, Anne Felden, Lucas Esclapez, Julia
  Ream, Marc T. Henry de Frahan, Jon Rood, Marc Day},
    journal={arXiv preprint arXiv:2405.05974},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.05974},
    primaryClass={physics.flu-dyn cs.SC physics.chem-ph}
}