Load balancing in particle simulations is a well-researched field, but its effect on molecular-continuum coupled simulations is comparatively less explored. In this work, we implement static load balancing into the macro-micro-coupling tool (MaMiCo), a software for molecular-continuum coupling, and demonstrate its effectiveness in two classes of experiments by coupling with the particle simulation software ls1 mardyn. The first class comprises a liquid-vapour multiphase scenario, modelling evaporation of a liquid into vacuum and requiring load balancing due to heterogeneous particle distributions in space. The second class considers execution of molecular-continuum simulations on heterogeneous hardware, running at very different efficiencies. After a series of experiments with balanced and unbalanced setups, we find that, with our balanced configurations, we achieve a reduction in runtime by 44% and 55% respectively.

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Static Load Balancing for Molecular-Continuum Flow Simulations with Heterogeneous Particle Systems and on Heterogeneous Hardware

  • Amartya Das Sharma,
  • Louis Viot,
  • Piet Jarmatz,
  • Hauke Preuß,
  • Philipp Neumann

摘要

Load balancing in particle simulations is a well-researched field, but its effect on molecular-continuum coupled simulations is comparatively less explored. In this work, we implement static load balancing into the macro-micro-coupling tool (MaMiCo), a software for molecular-continuum coupling, and demonstrate its effectiveness in two classes of experiments by coupling with the particle simulation software ls1 mardyn. The first class comprises a liquid-vapour multiphase scenario, modelling evaporation of a liquid into vacuum and requiring load balancing due to heterogeneous particle distributions in space. The second class considers execution of molecular-continuum simulations on heterogeneous hardware, running at very different efficiencies. After a series of experiments with balanced and unbalanced setups, we find that, with our balanced configurations, we achieve a reduction in runtime by 44% and 55% respectively.