Norbert Podhorszki


  • Liu, Q., Logan,J., Tian, Y., Abbasi, H., Podhorszki, N., Choi, J. Y., Klasky, S., Tchoua, R., Loftstead, J., Oldfield, R., Parashar, M., Samatova, N., Schwan, K., Shoshani, A., Wolf, M., Wu, K., and Yu, W. (2014, May). Hello ADIOS: the challenges and lessons of developing leadership class I/O frameworks. Concurrency and Computation: Practice and Experience,26(7), 1453–1473.
  • J. Logan et al., "A Vision for Managing Extreme-Scale Data Hoards," 2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS), Dallas, TX, USA, 2019, pp. 1806-1817, doi: 10.1109/ICDCS.2019.00179.
  • J. Y. Choi et al., "A Co-Design Study Of Fusion Whole Device Modeling Using Code Coupling," 2019 IEEE/ACM 5th International Workshop on Data Analysis and Reduction for Big Scientific Data (DRBSD-5), Denver, CO, USA, 2019, pp. 35-41, doi: 10.1109/DRBSD-549595.2019.00011.
  • Logan, Jeremy, Mark Ainsworth, Chuck Atkins, Jieyang Chen, Jong Choi, Junmin Gu, James Kress et al. "Extending the Publish/Subscribe Abstraction for High-Performance I/O and Data Management at Extreme Scale." Data Engineering: 35.
  • S. Klasky et al., "A View from ORNL: Scientific Data Research Opportunities in the Big Data Age," 2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS), Vienna, 2018, pp. 1357-1368.

    doi: 10.1109/ICDCS.2018.00136

    keywords: {Big Data;parallel processing;scientific information systems;human-generated logs;large-data artifacts;enterprise space;HPC community;scientific community;ORNL;scientific Data research opportunities;Big Data age;computational science;Adaptable I/O System;Data visualization;Task analysis;Analytical models;Big Data;Data models;Computational modeling;Tomography;High Performance Computing;Publish/Subscribe;High Performance I/O;In Situ Visualization},
  • Junmin Gu, Scott Klasky, Norbert Podhorszki, Ji Qiang, Kesheng Wu
    Querying Large Scientific Data Sets with Adaptable IO System ADIOS, Asian Conference on Supercomputing Frontiers (SCFA) 2018: Supercomputing Frontiers pp 51-69