Publications

Peer-reviewed papers, preprints, and technical reports produced by the project. Where available, links to the DOI, preprint, and reproducibility artifacts are provided.

2026

• 2026
  Understanding Large-Scale HPC System Behavior Through Cluster-Based Visual Analytics
  A. Austin, Shilpika, Y. T. Linus Lam, Y-S. Kuo, V. Vishwanath, M. E. Papka, K-L. Ma
  ISC High Performance 2026 Research Paper Proceedings (41st International Conference).
  visualization time series monitoring DOI

2025

• 2025
  MFNetSim: A Multi-Fidelity Network Simulation Framework for Multi-Traffic Modeling of Dragonfly Systems
  X. Wang, K. Brown, R. Ross, C. Carothers, and Z. Lan
  ACM Transactions on Modeling and Computer Simulation (TOMACS), to appear, 2025. Presented to DOE in April 2024.
  network simulation multi-fidelity dragonfly DOI
• 2025
  CQSim+: Symbiotic Simulation for Multi-Resource Scheduling in High-Performance Computing
  Y. Kurkure, S. Sharma, X. Wang, M. Papka, and Z. Lan
  SIGSIM PADS, to appear, 2025. Presented to DOE in November 2024.
  scheduling symbiotic simulation HPC DOI
• 2025
  Analyzing a Lifetime of Failures on a Cray XC40 Supercomputer
  K. Brown, T. Mallick, Z. Lan, R. Ross, and C. D. Carothers
  2025 Cray User Group (CUG) Conference, to appear.
  failure analysis resilience HPC DOI

2024

• 2024
  Hybrid PDES Simulation of HPC Networks Using Zombie Packets
  E. Cruz-Camacho, K. Brown, X. Wang, X. Xu, K. Shu, Z. Lan, R. Ross, and C. D. Carothers
  ACM Transactions on Modeling and Computer Simulation (TOMACS), to appear, July 2024 (online). Work co-supported by the DOE KRONOS project.
  PDES network simulation HPC DOI
• 2024
  Predictive Modeling of Application Runtime in Dragonfly Systems
  Pietro Lodi Rizzini
  MS Thesis, University of Illinois Chicago, December 2024. Part of the thesis investigates an integrated graph neural network and Time-LLM model as a surrogate model for accelerating PDES; a related conference paper appears in Dynamic Data Driven Applications Systems (DDDAS 2024), Springer LNCS.
  thesis surrogate models dragonfly DOI

Citing This Work

If you use the project's tools, datasets, or results, please cite the relevant publication above. A machine-readable CITATION.cff file is provided in each source repository.