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Enabling AI-Accelerated Multiscale Modeling of Thrombogenesis at Millisecond and Molecular Resolutions on Supercomputers

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High Performance Computing (ISC High Performance 2021)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12728))

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Abstract

We report the first congruent integration of HPC, AI, and multiscale modeling (MSM) for solving a mainstream biomechanical problem of thrombogenesis involving 6 million particles at record molecular-scale resolutions in space and at simulation rates of milliseconds per day. The two supercomputers, the IBM Summit-like AiMOS and our University’s SeaWulf, are used for scalability analysis of, and production runs with, the LAMMPS with our customization and AI augmentation and they attained optimal simulation speeds of 3,077 µs/day and 266 µs/day respectively. The long-time and large scales simulations enable the first study of the integrated platelet flowing, flipping, aggregating dynamics in one dynamically-coupled production run. The platelets’ angular and translational speeds, membrane particles’ speeds, and the membrane stress distributions are presented for the analysis of platelets’ aggregations.

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Acknowledgement

The project is supported by the SUNY-IBM Consortium Award, IPDyna: Intelligent Platelet Dynamics, FP00004096 (PI: Y. Deng, Co-PI: P. Zhang). The simulations were conducted on the AiMOS at Rensselaer Polytechnic Institute and the SeaWulf at Stony Brook University.

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Correspondence to Yuefan Deng .

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Zhu, Y., Zhang, P., Han, C., Cong, G., Deng, Y. (2021). Enabling AI-Accelerated Multiscale Modeling of Thrombogenesis at Millisecond and Molecular Resolutions on Supercomputers. In: Chamberlain, B.L., Varbanescu, AL., Ltaief, H., Luszczek, P. (eds) High Performance Computing. ISC High Performance 2021. Lecture Notes in Computer Science(), vol 12728. Springer, Cham. https://doi.org/10.1007/978-3-030-78713-4_13

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  • DOI: https://doi.org/10.1007/978-3-030-78713-4_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-78712-7

  • Online ISBN: 978-3-030-78713-4

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