We discuss the design and development of a parallel code for Large Eddy Simulation (LES) by exploiting libraries for sparse matrix computations. We formulate a numerical proce- dure for the LES of turbulent channel flows, based on an approximate projection method, in terms of linear algebra operators involving sparse matrices and vectors. Then we imple- ment the procedure using general-purpose linear algebra libraries as building blocks. This approach allows to pursue goals such as modularity, accuracy and robustness, as well as easy and fast exploitation of parallelism, with a relatively low coding effort. The parallel LES code developed in this work, named SParC-LES (Sparse Parallel Computation-based LES), exploits two parallel libraries: PSBLAS, providing basic sparse matrix operators and Krylov solvers, and MLD2P4, providing a suite of algebraic multilevel Schwarz preconditioners. Numerical experiments, concerning the simulation by SParC-LES of a turbulent flow in a plane channel, confirm that the LES code can achieve a satisfactory parallel performance. This supports our opinion that the software design methodology used to build SParC-LES yields a very good tradeoff between the exploitation of the computational power of parallel computers and the amount of coding effort.
SparC-LES: Enabling Large Eddy Simulations with Parallel Sparse Matrix Computation Tools
P D'Ambra;
2015
Abstract
We discuss the design and development of a parallel code for Large Eddy Simulation (LES) by exploiting libraries for sparse matrix computations. We formulate a numerical proce- dure for the LES of turbulent channel flows, based on an approximate projection method, in terms of linear algebra operators involving sparse matrices and vectors. Then we imple- ment the procedure using general-purpose linear algebra libraries as building blocks. This approach allows to pursue goals such as modularity, accuracy and robustness, as well as easy and fast exploitation of parallelism, with a relatively low coding effort. The parallel LES code developed in this work, named SParC-LES (Sparse Parallel Computation-based LES), exploits two parallel libraries: PSBLAS, providing basic sparse matrix operators and Krylov solvers, and MLD2P4, providing a suite of algebraic multilevel Schwarz preconditioners. Numerical experiments, concerning the simulation by SParC-LES of a turbulent flow in a plane channel, confirm that the LES code can achieve a satisfactory parallel performance. This supports our opinion that the software design methodology used to build SParC-LES yields a very good tradeoff between the exploitation of the computational power of parallel computers and the amount of coding effort.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


