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Temporal Causal Graph Discovery in Complex HPC Network Traffic Simulations (poster)
Authors: Ilamathy, S., Joy, R. A., Dearing, M.T., Lan, Z.
Publication: The 12th Greater Chicago Area Systems Research Workshop (GCASR), Chicago, IL URL: https://gcasr.org/2025/posters Motivation: • Parallel Discrete Event Simulations (PDES) offers accurate HPC simulations but is computationally intensive and slow to scale. • Surrogate models can accelerate simulations, and we explore if causal insights can improve their long-term forecasting stability. Research Questions: • Can Causal Signals hidden in HPC simulations unlock better forecasting? • Can different Causal Discovery methods identify key drivers for accurate surrogate forecasting? Date: May 8, 2025 Document: View PDF |
