Scalable multiscale modeling of platelets with 100 million particles

Han, Changnian; Zhang, Peng; Zhu, Yicong; Cong, Guojing; Kozloski, James R.; Yang, Chih Chieh; Zhang, Leili; Deng, Yuefan

doi:10.1007/s11227-022-04648-4

Scalable multiscale modeling of platelets with 100 million particles

Journal Article · Wed Jun 29 00:00:00 EDT 2022 · Journal of Supercomputing

DOI:https://doi.org/10.1007/s11227-022-04648-4· OSTI ID:1876268

Han, Changnian ^[1]; Zhang, Peng ^[1]; Zhu, Yicong ^[1]; Cong, Guojing ^[2]; Kozloski, James R. ^[3]; Yang, Chih Chieh ^[3]; Zhang, Leili ^[3]; ^[4]

Stony Brook Univ., NY (United States)
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
IBM Thomas J. Watson Research Center, Yorktown Heights, NY (United States)
Stony Brook Univ., NY (United States); New York University, Abu Dhabi (United Arab Emirates)

Here, we developed the core components of the AI-aided multiple time stepping algorithm for multiscale modeling of cell dynamics. This algorithm was implemented and analyzed on two supercomputer architectures with an application of simulating the aggregation of 250 platelets, or 102 million particles. To scale on these computers with complex memory and network architectures with GPUs, we devised a biomechanics-informed task mapping scheme to optimize load imbalance, communications, and memory utilization. Our simulations, scaling well up to 192 nodes on a Summit-like supercomputer with a peak speed of 11 petaflops, achieved a rate of 423 μs/day which is 500 times faster than the conventional algorithm using static time step and this has enabled studies of record size blood clots at record spatial–temporal resolutions. Additionally, we discovered the sensitive dependence of the scalability and execution time on the methods of decomposition, CPU–GPU coupling, and task mapping.

View Accepted Manuscript (DOE)

Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE; SUNY-IBM Consortium

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 1876268

Journal Information:: Journal of Supercomputing, Journal Name: Journal of Supercomputing Journal Issue: 1 Vol. TBD; ISSN 0920-8542

Publisher:: SpringerCopyright Statement

Country of Publication:: United States

Language:: English

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