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DTSTART;TZID=America/Denver:20231116T133000
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UID:submissions.supercomputing.org_SC23_sess182_pap548@linklings.com
SUMMARY:Cloud Computing to Enable Wearable-Driven Longitudinal Hemodynamic
  Maps
DESCRIPTION:Cyrus Tanade, Emily Rakestraw, and William Ladd (Duke Universi
 ty); Erik Draeger (Lawrence Livermore National Laboratory (LLNL)); and Ama
 nda Randles (Duke University)\n\nTracking hemodynamic responses to treatme
 nt and stimuli over long periods remains a grand challenge. Moving from es
 tablished single-heartbeat technology to longitudinal profiles would requi
 re continuous data describing how the patient’s state evolves, new methods
  to extend the temporal domain over which flow is sampled, and high-throug
 hput computing resources. While personalized digital twins can accurately 
 measure 3D hemodynamics over several heartbeats, state-of-the-art methods 
 would require hundreds of years of wallclock time on leadership scale syst
 ems to simulate one day of activity. To address these challenges, we propo
 se a cloud-based, parallel-in-time framework leveraging continuous data fr
 om wearable devices to capture the first 3D patient-specific, longitudinal
  hemodynamic maps. We demonstrate the validity of our method by establishi
 ng ground truth data for 750 beats and comparing the results. Our cloud-ba
 sed framework is based on an initial fixed set of simulations to enable th
 e wearable-informed creation of personalized longitudinal hemodynamic maps
 .\n\nTag: Algorithms, Cloud Computing, Distributed Computing, Heterogeneou
 s Computing, Large Scale Systems, State of the Practice\n\nRegistration Ca
 tegory: Tech Program Reg Pass\n\nReproducibility Badges: Artifact Availabl
 e, Artifact Functional\n\nSession Chair: Mahdieh Ghazimirsaeed (Advanced M
 icro Devices (AMD) Inc)\n\n
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