TY - JOUR
T1 - Sparse matrix factorization in the implicit finite element method on petascale architecture
AU - Koric, Seid
AU - Gupta, Anshul
N1 - Funding Information:
The authors would like to thank the Private Sector Program and the Blue Waters sustained-petascale computing project at the National Center for Supercomputing Applications (NCSA). Blue Waters is supported by the National Science Foundation (award numbers OCI 07-25070 and ACI-1238993 ) and the state of Illinois.
Publisher Copyright:
© 2016 Elsevier B.V.
PY - 2016/4/15
Y1 - 2016/4/15
N2 - The performance of the massively parallel direct multifrontal solver Watson Sparse Matrix Package (WSMP) for solving large sparse systems of linear equations arising in implicit finite element method on unstructured (free) meshes in solid mechanics was evaluated on one of the most powerful supercomputers currently available to the open science community-the sustained petascale high performance computing system of Blue Waters. We have performed full-scale benchmarking tests up to 65,536 cores using assembled global stiffness matrices and load vectors ranging from 11 to 40 million unknowns extracted from "real-world" commercial implicit finite element analysis (FEA) applications. The results show that a direct multifrontal factorization method with a hybrid parallel implementation in WSMP performs exceedingly well on a petascale high-performance computing (HPC) system, and delivers superior factorization time and parallel scalability, thus opening the door for the high fidelity modeling of complex industrial structures and assemblies in real scale.
AB - The performance of the massively parallel direct multifrontal solver Watson Sparse Matrix Package (WSMP) for solving large sparse systems of linear equations arising in implicit finite element method on unstructured (free) meshes in solid mechanics was evaluated on one of the most powerful supercomputers currently available to the open science community-the sustained petascale high performance computing system of Blue Waters. We have performed full-scale benchmarking tests up to 65,536 cores using assembled global stiffness matrices and load vectors ranging from 11 to 40 million unknowns extracted from "real-world" commercial implicit finite element analysis (FEA) applications. The results show that a direct multifrontal factorization method with a hybrid parallel implementation in WSMP performs exceedingly well on a petascale high-performance computing (HPC) system, and delivers superior factorization time and parallel scalability, thus opening the door for the high fidelity modeling of complex industrial structures and assemblies in real scale.
KW - Factorization
KW - Finite element method
KW - Petascale high performance computing
KW - Sparse linear solvers
KW - Unstructured mesh
UR - http://www.scopus.com/inward/record.url?scp=84957921949&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84957921949&partnerID=8YFLogxK
U2 - 10.1016/j.cma.2016.01.011
DO - 10.1016/j.cma.2016.01.011
M3 - Article
AN - SCOPUS:84957921949
SN - 0374-2830
VL - 302
SP - 281
EP - 292
JO - Computer Methods in Applied Mechanics and Engineering
JF - Computer Methods in Applied Mechanics and Engineering
ER -