TY - GEN
T1 - Enabling AI-Accelerated Multiscale Modeling of Thrombogenesis at Millisecond and Molecular Resolutions on Supercomputers
AU - Zhu, Yicong
AU - Zhang, Peng
AU - Han, Changnian
AU - Cong, Guojing
AU - Deng, Yuefan
N1 - Publisher Copyright:
© 2021, Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - 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.
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.
KW - AI
KW - High-performance computing
KW - Multiscale modeling
KW - Platelet aggregation
UR - http://www.scopus.com/inward/record.url?scp=85111453686&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85111453686&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-78713-4_13
DO - 10.1007/978-3-030-78713-4_13
M3 - Conference contribution
AN - SCOPUS:85111453686
SN - 9783030787127
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 237
EP - 254
BT - High Performance Computing - 36th International Conference, ISC High Performance 2021, Proceedings
A2 - Chamberlain, Bradford L.
A2 - Chamberlain, Bradford L.
A2 - Varbanescu, Ana-Lucia
A2 - Ltaief, Hatem
A2 - Luszczek, Piotr
PB - Springer Science and Business Media Deutschland GmbH
T2 - 36th International Conference on High Performance Computing, ISC High Performance 2021
Y2 - 24 June 2021 through 2 July 2021
ER -