Sparse matrix factorization in the implicit finite element method on petascale architecture

Seid Koric, Anshul Gupta

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish (US)
Pages (from-to)281-292
Number of pages12
JournalComputer Methods in Applied Mechanics and Engineering
Volume302
DOIs
StatePublished - Apr 15 2016

Keywords

  • Factorization
  • Finite element method
  • Petascale high performance computing
  • Sparse linear solvers
  • Unstructured mesh

ASJC Scopus subject areas

  • Computational Mechanics
  • Mechanics of Materials
  • Mechanical Engineering
  • General Physics and Astronomy
  • Computer Science Applications

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