Session

DescriptionMolecular dynamics (MD) simulations are pivotal in computational science, offering atomistic insights into complex systems across biophysics, materials science, and chemistry. However, the exponential growth in data generation and the increasing heterogeneity of supercomputing systems pose significant challenges for traditional MD workflows. This minisymposium presents cutting- edge strategies for optimizing MD dataflows to enable real-time analysis, leveraging in situ and in transit techniques alongside emerging technologies like machine learning, GPUs, and quantum computing. The session features diverse speakers from leading global institutions. Florence Tama (RIKEN, Japan) discusses scalable workflows for Cryo-EM and MD integration to study biomolecular con-formational variability. Michel A. Cuendet (SIB, Switzerland) introduces runtime strategies to improve ensemble MD efficiency by terminating unproductive trajectories. Early-career researcher Lo¨ıc Pottier (LLNL, USA) highlights the MuMMI framework for machine learning-driven multi- scale MD workflows. Ivona Brandi´c (TU Wien, Austria) explores hybrid classical/quantum systems and adaptive cloud-based MD workflows. Aligned with PASC25’s theme, “Supercomputing for Sustainable Development,” the session emphasizes sustainable computing practices and supports multiple UN SDGs, including SDG 9 (Industry, Innovation, and Infrastructure). Attendees will gain valuable insights into advancing MD workflows for the future of HPC-driven scientific discovery.