Toward GPU accelerated topology optimization on unstructured meshes

Tomás Zegard, Glaucio H. Paulino

Research output: Contribution to journalArticlepeer-review

34 Scopus citations

Abstract

The present work investigates the feasibility of finite element methods and topology optimization for unstructured meshes in massively parallel computer architectures, more specifically on Graphics Processing Units or GPUs. Challenges in the parallel implementation, like the parallel assembly race condition, are discussed and solved with simple algorithms, in this case greedy graph coloring. The parallel implementation for every step involved in the topology optimization process is benchmarked and compared against an equivalent sequential implementation. The ultimate goal of this work is to speed up the topology optimization process by means of parallel computing using off-the-shelf hardware. Examples are compared with both a standard sequential version of the implementation and a massively parallel version to better illustrate the advantages and disadvantages of this approach.

Original languageEnglish (US)
Pages (from-to)473-485
Number of pages13
JournalStructural and Multidisciplinary Optimization
Volume48
Issue number3
DOIs
StatePublished - Sep 2013
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Software
  • Control and Systems Engineering
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design
  • Control and Optimization

Keywords

  • CUDA
  • FEM
  • Finite element method
  • GPU
  • Graphics processing units
  • Topology optimization

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