Toward GPGPU accelerated human electromechanical cardiac simulations

Guillermo Vigueras, Ishani Roy, Andrew Cookson, Jack Lee, Nicolas Smith, David Nordsletten

Research output: Contribution to journalArticlepeer-review

11 Citations (SciVal)

Abstract

In this paper, we look at the acceleration of weakly coupled electromechanics using the graphics processing unit (GPU). Specifically, we port to the GPU a number of components of CHeart--a CPU-based finite element code developed for simulating multi-physics problems. On the basis of a criterion of computational cost, we implemented on the GPU the ODE and PDE solution steps for the electrophysiology problem and the Jacobian and residual evaluation for the mechanics problem. Performance of the GPU implementation is then compared with single core CPU (SC) execution as well as multi-core CPU (MC) computations with equivalent theoretical performance. Results show that for a human scale left ventricle mesh, GPU acceleration of the electrophysiology problem provided speedups of 164 × compared with SC and 5.5 times compared with MC for the solution of the ODE model. Speedup of up to 72 × compared with SC and 2.6 × compared with MC was also observed for the PDE solve. Using the same human geometry, the GPU implementation of mechanics residual/Jacobian computation provided speedups of up to 44 × compared with SC and 2.0 × compared with MC.

Original languageEnglish
Pages (from-to)117-34
Number of pages18
JournalInternational Journal for Numerical Methods in Biomedical Engineering
Volume30
Issue number1
DOIs
Publication statusPublished - 31 Jan 2014

Keywords

  • Algorithms
  • Cardiac Electrophysiology
  • Computer Graphics
  • Computer Simulation
  • Heart
  • Humans
  • Models, Theoretical
  • Journal Article
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

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