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Application of high-performance computing to numerical simulation of human movement

F C Anderson1, J M Ziegler, M G Pandy

  • 1Department of Kinesiology, University of Texas at Austin 78712, USA.

Journal of Biomechanical Engineering
|February 1, 1995
PubMed
Summary

Supercomputers like the Cray and Intel significantly reduce computation time for human movement optimization problems. A hybrid architecture combining parallel and vector processing offers the most efficient solution for complex biomechanical simulations.

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Area of Science:

  • Biomechanics
  • Computational Science
  • Supercomputing

Background:

  • Solving large-scale optimization problems in human movement is computationally intensive.
  • Previous methods on conventional serial machines required extensive processing time.

Purpose of the Study:

  • To evaluate the feasibility of using massively-parallel and vector-processing supercomputers for human movement optimization.
  • To compare the computational expense of different supercomputer architectures for gait analysis.

Main Methods:

  • Modeled the human body as a 14 degree-of-freedom linkage with 46 musculotendinous units.
  • Compared computational time on a serial machine (SGI Iris), a MIMD parallel machine (Intel iPSC/860), and a parallel-vector machine (Cray Y-MP).
  • Calculated optimal controls for the single support phase of gait.
Keywords:
NASA Center ARCNASA Discipline MusculoskeletalNASA Discipline Number 26-10NASA Program Space Physiology and Countermeasures

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Main Results:

  • Gait optimization on the SGI Iris could take up to 3 months of CPU time.
  • The Cray Y-MP reduced computation to approximately 77 CPU hours.
  • The Intel iPSC/860 reduced computation to approximately 88 CPU hours.
  • Intel excelled at derivative computations; Cray excelled at parameter optimization.

Conclusions:

  • Massively-parallel and parallel-vector processing supercomputers can solve large-scale human movement optimization problems efficiently.
  • A hybrid system integrating vector processing with MIMD parallel architecture is ideal for complex optimal control problems.