In the present study, we demonstrated a parallel P2P1 finite element scheme with a four-step fractional splitting approach to conduct a multiscale coronary flow simulation. The three-dimensional (3D) computational fluid dynamics (CFD) for patient-specific coronary artery flow and zero-dimensional (0D) lumped-parameter network (LPN) modeling for distal coronary beds was fully coupled, and an MPI parallel algorithm based on domain decomposition was applied. A parallel conjugate gradient (CG)-LPN subroutine for the 3D-0D coupled system with a monolithic scheme was derived, and it provides a correct pressure solution that may not be obtained by the conventional CG solver, particularly when the subdomain division intersects the 3D-0D coupling outlet. The overall computing time for parallel CG-LPN does not show a noticeable difference from the conventional CG solver, despite the extra MPI calls for data transfer at the interfaces of subdomains. For the BiCGSTAB solver, the block ILU(0) preconditioner showed favorable performance for a high density mesh compared with the simple Jacobi preconditioner. MPI_COMM is a major bottleneck that saturates the overall parallel performance at high core count, but a computing time of less than 10 min per cardiac cycle on a medium density mesh could be attained for a patient-specific coronary flow simulation using 60 CPU cores run in parallel, which is in an acceptable range for clinical practice. Further tests of accuracy are needed with a large set of patients to enable wide use of the proposed technique in helping to make interventional decisions in routine clinical practice for coronary stenotic lesions.
Bibliographical noteFunding Information:
This work was supported by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIP) (no. R0101-15-0171).
This work was supported by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government ( MSIP ) (no. R0101-15-0171 ).
All Science Journal Classification (ASJC) codes
- Computer Science(all)