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Publications

Balsam is a community project developed at Argonne Leadership Computing Facility. If you find it useful for your computational science work, please include the following citation in your publications.

  • M. Salim, T. D. Uram, J.T. Childers, P. Balaprakash, V. Vishwanath, M. Papka. Balsam: Automated Scheduling and Execution of Dynamic, Data-Intensive HPC Workflows. In Proceedings of the 8th Workshop on Python for High-Performance and Scientific Computing. ACM Press, 2018.

  • R. Vescovi, H. Li, J. Kinnison, M. Keceli, M. Salim, N. Kasthuri, T. D. Uram, N. Ferrier, Toward an Automated HPC Pipeline for Processing Large Scale Electron Microscopy Data, 2020 IEEE/ACM 2nd Annual Workshop on Extreme-scale Experiment-in-the-Loop Computing (XLOOP), 2020, pp. 16-22, doi: 10.1109/XLOOP51963.2020.00008.

  • M. Salim, T. D. Uram, J. T. Childers, V. Vishwanath and M. Papka, Balsam: Near Real-Time Experimental Data Analysis on Supercomputers, 2019 IEEE/ACM 1st Annual Workshop on Large-scale Experiment-in-the-Loop Computing (XLOOP), 2019, pp. 26-31, doi: 10.1109/XLOOP49562.2019.00010.

  • A. Brace, M. Salim, V. Subbiah, H. Ma, M. Emani, A. Trifa, A. R. Clyde, C. Adams, T. D. Uram, H. Yoo, A. Hock, J. Liu, V. Vishwanath, and A. Ramanathan. Stream-AI-MD: streaming AI-driven adaptive molecular simulations for heterogeneous computing platforms. Proceedings of the Platform for Advanced Scientific Computing Conference. Association for Computing Machinery, New York, NY, USA, Article 6, 1–13. DOI:https://doi.org/10.1145/3468267.3470578

  • A. Al-Saadi, D. H. Ahn, Y. Babuji, K. Chard, J. Corbett, M. Hategan, S. Herbein, S. Jha, D. Laney, A. Merzky, T. Munson, M. Salim, M. Titov, M. Turilli, T. D. Uram, J. M. Wozniak, ExaWorks: Workflows for Exascale, 2021 IEEE Workshop on Workflows in Support of Large-Scale Science (WORKS), 2021, pp. 50-57, doi: 10.1109/WORKS54523.2021.00012.

  • S. Hudson, J. Larson, J. -L. Navarro and S. M. Wild, libEnsemble: A Library to Coordinate the Concurrent Evaluation of Dynamic Ensembles of Calculations, in IEEE Transactions on Parallel and Distributed Systems, vol. 33, no. 4, pp. 977-988, 1 April 2022, doi: 10.1109/TPDS.2021.3082815.

  • P. Balaprakash, R. Egele, M. Salim, S. Wild, V. Vishwanath, F. Xia, T. Brettin, and R. Stevens. Scalable reinforcement-learning-based neural architecture search for cancer deep learning research. In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC '19). Association for Computing Machinery, New York, NY, USA, Article 37, 1–33. DOI:https://doi.org/10.1145/3295500.3356202

  • P. Balaprakash, M. Salim, T. D. Uram, V. Vishwanath and S. M. Wild, DeepHyper: Asynchronous Hyperparameter Search for Deep Neural Networks, 2018 IEEE 25th International Conference on High Performance Computing (HiPC), 2018, pp. 42-51, doi: 10.1109/HiPC.2018.00014.

  • M. Kostuk, T. D. Uram, T. Evans, D. M. Orlov, M. E. Papka, and D. Schissel, Automatic Between-Pulse Analysis of DIII-D Experimental Data Performed Remotely on a Supercomputer at Argonne Leadership Computing Facility. United States: N. p., 2018. Web. https://doi.org/10.1080/15361055.2017.1390388.

  • J. T. Childers, T. D. Uram, D. Benjamin, T. J. LeCompte, and M. E. Papka. An Edge Service for Managing HPC Workflows. In Proceedings of the Fourth International Workshop on HPC User Support Tools (HUST'17). Association for Computing Machinery, New York, NY, USA, Article 1, 1–8. DOI:https://doi.org/10.1145/3152493.3152557

  • T. D. Uram, J. T. Childers, T. J. LeCompte, M. E. Papka, D. Benjamin, Achieving production-level use of HEP software at the Argonne Leadership Computing Facility. Journal of Physics: Conference Series. 664. 062063. 10.1088/1742-6596/664/6/062063.