SC23 Proceedings

The International Conference for High Performance Computing, Networking, Storage, and Analysis

ACM Student Research Competition Poster Archive

Cloud Computing at Scale: Tracking 4.5 Million Heartbeats of 3D Coronary Flow via the Longitudinal Hemodynamic Mapping Framework

Student: Cyrus Tanade (Duke University)
Supervisor: Amanda Randles (Duke University)

Abstract: Tracking hemodynamic responses to treatment and stimuli for long periods is a grand challenge. Moving from established single-heartbeat technology to longitudinal profiles would require continuous data reflecting a patient's evolving state, methods to extend the temporal domain that could be feasibly computed, and high-throughput resources. Although personalized models can accurately measure 3D hemodynamics over single heartbeats, state-of-the-art methods would require centuries of runtime on leadership-class systems to simulate one day of activity. We are establishing the Longitudinal Hemodynamic Mapping Framework (LHMF), which combines patient-specific models, wearables, and cloud computing to enable the first digital twins that capture longitudinal hemodynamic maps (LHMs). We demonstrate validity through comparison with ground truth data for 750 beats. We applied LHMF to generate the first LHM of coronary arteries spanning 4.5 million heartbeats. LHMF relies on an initial fixed set of representative simulations to enable the computationally tractable creation of LHM over heterogeneous systems.

ACM-SRC Semi-Finalist: no

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