Abstract
We have developed an AI-aided multiple time stepping (AI-MTS) algorithm and multiscale modeling framework (AI-MSM) and implemented them on the AiMOS supercomputer. AI-MSM is the first of its kind to integrate multi-physics, including intra-platelet, inter-platelet, and fluid-platelet interactions, into one system. It has simulated a record-setting multiscale blood clotting model of 102 million particles, of which 70 flowing and 180 aggregating platelets, under dissipative particle dynamics to coarse-grained molecular dynamics. By adaptively adjusting timestep sizes to match the characteristic time scales of the underlying dynamics, AI-MTS optimally balances speeds and accuracies of the simulations.
Original language | English |
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Article number | 108718 |
Journal | Computer Physics Communications |
Volume | 287 |
DOIs | |
State | Published - Jun 2023 |
Funding
This project is supported by the SUNY-IBM Consortium Award, IPDyna: Intelligent Platelet Dynamics, FP00004096 (PI: Y. Deng). The simulations in this study were conducted on the AiMOS supercomputer at Rensselaer Polytechnic Institute and the SeaWulf Cluster at Stony Brook University (PIs: Y. Deng and P. Zhang). This project is supported by the SUNY-IBM Consortium Award, IPDyna: Intelligent Platelet Dynamics , FP00004096 (PI: Y. Deng). The simulations in this study were conducted on the AiMOS supercomputer at Rensselaer Polytechnic Institute and the SeaWulf Cluster at Stony Brook University (PIs: Y. Deng and P. Zhang).
Keywords
- Artificial intelligence
- Blood clotting
- HPC
- Multiscale modeling