Sparse matrix factorization on massively parallel computers
Anshul Gupta, Seid Koric, et al.
SC 2009
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.
Anshul Gupta, Seid Koric, et al.
SC 2009
Anshul Gupta, Thomas George
SIAM Journal on Scientific Computing
Thomas George, Vaibhav Saxena, et al.
IPDPS 2011
Anshul Gupta, Seid Koric, et al.
SC 2009