在OpenSim Moco中使用并行计算对肌肉骨模拟的计算性能
Alex N Denton1, Brian R Umberger1
1School of Kinesiology, University of Michigan, Ann Arbor, Michigan, USA.
International journal for numerical methods in biomedical engineering
|September 25, 2023
概括
在OpenSim Moco中的多核并行计算显著加快了肌肉骨模拟. 对于最佳控制的人类运动模型,使用大约六个处理器核心实现了大部分的性能增长.
科学领域:
- 生物力学 生物力学
- 计算科学 计算科学
- 人类运动分析 人类运动分析
背景情况:
- 最佳控制肌肉骨模拟对于理解人类运动至关重要.
- 高计算需求限制了模拟性能.
- 与CasADi一起的OpenSim Moco提供了并行处理的潜力.
研究的目的:
- 在OpenSim Moco中评估并行与串行处理的计算加速度.
- 用多核处理器来量化性能增长,用于人类运动模拟.
主要方法:
- 在OpenSim Moco.中使用多达18个核心运行模拟.
- 测试了各种时网密度和初始猜测策略.
- 分析了多种肌肉骨模型和运动类型 (走路,伸手).
主要成果:
- 与串行处理相比,并行处理实现了1.7至7.7倍的速度提升.
- 最大加速度取决于问题,最多的收益来自6核.
- 较细的时间网格通常会产生更大的并行加速度.
结论:
- 在OpenSim Moco中的多核处理可以大大减少计算时间,以实现最佳的控制模拟.
- 性能改进是特定于模拟问题的.
- 用户可能需要进行实验以实现最佳的计算性能.
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