TY - GEN
T1 - A next-generation discontinuous galerkin fluid dynamics solver with application to high-resolution lung airflow simulations
AU - Kronbichler, Martin
AU - Fehn, Niklas
AU - Munch, Peter
AU - Bergbauer, Maximilian
AU - Wichmann, Karl Robert
AU - Geitner, Carolin
AU - Allalen, Momme
AU - Schulz, Martin
AU - Wall, Wolfgang A.
N1 - Publisher Copyright:
© 2021 IEEE Computer Society. All rights reserved.
PY - 2021/11/14
Y1 - 2021/11/14
N2 - We present a novel, highly scalable and optimized solver for turbulent flows based on high-order discontinuous Galerkin discretizations of the incompressible Navier Stokes equations aimed to minimize time-To-solution. The solver uses explicit-implicit time integration with variable step size. The central algorithmic component is the matrix-free evaluation of discretized finite element operators. The node-level performance is optimized by sum-factorization kernels for tensor-product elements with unique algorithmic choices that reduce the number of arithmetic operations, improve cache usage, and vectorize the arithmetic work across elements and faces. These ingredients are integrated into a framework scalable to the massive parallelism of supercomputers by the use of optimal-complexity linear solvers, such as mixed-precision, hybrid geometric-polynomial-Algebraic multigrid solvers for the pressure Poisson problem. The application problem under consideration are fluid dynamical simulations of the human respiratory system under mechanical ventilation conditions, using unstructured/structured adaptively refined meshes for geometrically complex domains typical of biomedical engineering.
AB - We present a novel, highly scalable and optimized solver for turbulent flows based on high-order discontinuous Galerkin discretizations of the incompressible Navier Stokes equations aimed to minimize time-To-solution. The solver uses explicit-implicit time integration with variable step size. The central algorithmic component is the matrix-free evaluation of discretized finite element operators. The node-level performance is optimized by sum-factorization kernels for tensor-product elements with unique algorithmic choices that reduce the number of arithmetic operations, improve cache usage, and vectorize the arithmetic work across elements and faces. These ingredients are integrated into a framework scalable to the massive parallelism of supercomputers by the use of optimal-complexity linear solvers, such as mixed-precision, hybrid geometric-polynomial-Algebraic multigrid solvers for the pressure Poisson problem. The application problem under consideration are fluid dynamical simulations of the human respiratory system under mechanical ventilation conditions, using unstructured/structured adaptively refined meshes for geometrically complex domains typical of biomedical engineering.
KW - High-order discontinuous Galerkin
KW - Matrix-free algorithms
KW - Multigrid
KW - Time-To-solution
UR - http://www.scopus.com/inward/record.url?scp=85119953331&partnerID=8YFLogxK
U2 - 10.1145/3458817.3476171
DO - 10.1145/3458817.3476171
M3 - Conference contribution
AN - SCOPUS:85119953331
T3 - International Conference for High Performance Computing, Networking, Storage and Analysis, SC
BT - Proceedings of SC 2021
PB - IEEE Computer Society
T2 - 33rd International Conference for High Performance Computing, Networking, Storage and Analysis: Science and Beyond, SC 2021
Y2 - 14 November 2021 through 19 November 2021
ER -