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

Yicong Zhu; Peng Zhang; Changnian Han; Guojing Cong; Yuefan Deng

doi:10.1007/978-3-030-78713-4_13

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

Yicong Zhu, Peng Zhang, Changnian Han, Guojing Cong, Yuefan Deng

Learning Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

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.

Original language	English
Title of host publication	High Performance Computing - 36th International Conference, ISC High Performance 2021, Proceedings
Editors	Bradford L. Chamberlain, Bradford L. Chamberlain, Ana-Lucia Varbanescu, Hatem Ltaief, Piotr Luszczek
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	237-254
Number of pages	18
ISBN (Print)	9783030787127
DOIs	https://doi.org/10.1007/978-3-030-78713-4_13
State	Published - 2021
Event	36th International Conference on High Performance Computing, ISC High Performance 2021 - Virtual, Online Duration: Jun 24 2021 → Jul 2 2021

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12728 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	36th International Conference on High Performance Computing, ISC High Performance 2021
City	Virtual, Online
Period	06/24/21 → 07/2/21

Funding

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. 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.

Keywords

AI
High-performance computing
Multiscale modeling
Platelet aggregation

Access to Document

10.1007/978-3-030-78713-4_13

Cite this

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 B. L. Chamberlain, B. L. Chamberlain, A.-L. Varbanescu, H. Ltaief, & P. Luszczek (Eds.), High Performance Computing - 36th International Conference, ISC High Performance 2021, Proceedings (pp. 237-254). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12728 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-78713-4_13

Zhu, Yicong ; Zhang, Peng ; Han, Changnian et al. / Enabling AI-Accelerated Multiscale Modeling of Thrombogenesis at Millisecond and Molecular Resolutions on Supercomputers. High Performance Computing - 36th International Conference, ISC High Performance 2021, Proceedings. editor / Bradford L. Chamberlain ; Bradford L. Chamberlain ; Ana-Lucia Varbanescu ; Hatem Ltaief ; Piotr Luszczek. Springer Science and Business Media Deutschland GmbH, 2021. pp. 237-254 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{6891bf51c4de4795a18f15eae823a025,

title = "Enabling AI-Accelerated Multiscale Modeling of Thrombogenesis at Millisecond and Molecular Resolutions on Supercomputers",

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{\textquoteright}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{\textquoteright} angular and translational speeds, membrane particles{\textquoteright} speeds, and the membrane stress distributions are presented for the analysis of platelets{\textquoteright} aggregations.",

keywords = "AI, High-performance computing, Multiscale modeling, Platelet aggregation",

author = "Yicong Zhu and Peng Zhang and Changnian Han and Guojing Cong and Yuefan Deng",

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doi = "10.1007/978-3-030-78713-4_13",

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editor = "Chamberlain, {Bradford L.} and Chamberlain, {Bradford L.} and Ana-Lucia Varbanescu and Hatem Ltaief and Piotr Luszczek",

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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 BL Chamberlain, BL Chamberlain, A-L Varbanescu, H Ltaief & P Luszczek (eds), High Performance Computing - 36th International Conference, ISC High Performance 2021, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12728 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 237-254, 36th International Conference on High Performance Computing, ISC High Performance 2021, Virtual, Online, 06/24/21. https://doi.org/10.1007/978-3-030-78713-4_13

Enabling AI-Accelerated Multiscale Modeling of Thrombogenesis at Millisecond and Molecular Resolutions on Supercomputers. / Zhu, Yicong; Zhang, Peng; Han, Changnian et al.
High Performance Computing - 36th International Conference, ISC High Performance 2021, Proceedings. ed. / Bradford L. Chamberlain; Bradford L. Chamberlain; Ana-Lucia Varbanescu; Hatem Ltaief; Piotr Luszczek. Springer Science and Business Media Deutschland GmbH, 2021. p. 237-254 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12728 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Deng, Yuefan

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AB - 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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Zhu Y, Zhang P, Han C, Cong G, Deng Y. Enabling AI-Accelerated Multiscale Modeling of Thrombogenesis at Millisecond and Molecular Resolutions on Supercomputers. In Chamberlain BL, Chamberlain BL, Varbanescu AL, Ltaief H, Luszczek P, editors, High Performance Computing - 36th International Conference, ISC High Performance 2021, Proceedings. Springer Science and Business Media Deutschland GmbH. 2021. p. 237-254. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-78713-4_13

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

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