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Mary works at the San Diego Supercomputer
Center in the Data-Enabled Scientific Computing Division, where she is the HPC/CI
Advanced Computing Training
Lead, and is responsible for developing and organizing educational and training materials to support the work of scientists running computational problems on HPC systems, including the SDSC Expanse and Voyager systems. Her research is focussed on computational science, parallel programming, advanced computational environments that support high-end scientific applications, and workforce development of the community of people who need to use HPC/CI resources. Thomas is PI or Co-PI of three NSF CyberTraining grants that focus on: developing cyberinfrastructure professionals who will facilitate researchers to access and use NSF CI resources and services (#2230127, PI); teach researchers best practices for developing scalable AI/ML applications (#2017767, PI); and developing taxonomies for a federated training materials repository (#2320977, Co-PI).
Mary works with graduate and undergraduate students through the SDSC HPC Students program. Her support and mentoring includes:
mentoring interns in parallel computing on the Expanse cluster; developing advanced web technologies for the SDSC Advanced Computing Training program; and
advising the IEEE Supercomputing Club,where she has sponsored several teams to participate in the annual Student Cluster Competitions at the annual Supercomputing conference. For more information, see https://www.sdsc.edu/~mthomas/index.html.
For information about HPC Students Internships, and current openings, see: https://www.sdsc.edu/~mthomas/internships.html
Mary is also a Research Faculty member at the Computational Sciences Research Center and the Department of Computer Science at San Diego State University.
See https://thomas.sdsu.edu for more information on her SDSU activities.
Current projects include:
Currently funded research projects:
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PI, NSF Award #2230127, CIP: Training and Developing a Research Computing and Data CI Professionals (RCD-CIP) Community
- PI, NSF Award #2017767, CyberTraining: Developing a Best Practices Training Program in Cyberinfrastructure-Enabled Machine Learning Research
- Co-PI, NSF Award #2320977, CyberTraining: Pilot: HPC ED: Building a Federated Repository and Increasing Access through Cybertraining
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SDSC PI, NSF Award #2346701, CC* Regional Computing: The California State University System Technology Infrastructure for Data Exploration (TIDE)
- SP, NSF Award #2320934,
CyberTraining: Implementation: Small: COMPrehensive Learning for end-users to Effectively utilize CyberinfraStructure (COMPLECS)
- SP, NSF Award #2112606, AI Institute for Intelligent CyberInfrastructure with Computational Learning in the Environment (ICICLE)
- SP, NSF Award #1928224, Expanse: Category I. Computing without Boundaries: Cyberinfrastructure for the Long Tail of Science
- SP, NSF Award #2404323, Cosmos: Category II: Democratizing the Accelerator Ecosystem for Science and Discovery
Past funded research projects:
Recent publications:
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Mary P Thomas, Susan Mehringer, Katharine Cahill, Charlie Dey, Brian Guilfoos, David Joiner, John-Paul Navarro, Jeaime H. Powell, and Richard Knepper. 2024. Building a Federated Catalog for CyberTraining Materials: The HPC-ED Pilot Project. In Practice and Experience in Advanced Research Computing 2024: Human Powered Computing (PEARC '24). Association for Computing Machinery, New York, NY, USA, Article 88, 1 to 5. https://doi.org/10.1145/3626203.3670586
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Robert S Sinkovits, Nicole Wolter, Marty Charles Kandes, Mary P Thomas, and Monica Sweet. 2024. COMPLECS: COMPrehensive Learning for end-users to Effectively utilize CyberinfraStructure. In Practice and Experience in Advanced Research Computing 2024: Human Powered Computing (PEARC '24). Association for Computing Machinery, New York, NY, USA, Article 87, 1 to 4. https://doi.org/10.1145/3626203.3670553
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Zixian Wang, Khai Vu, Miro Hodak, Aarush Mehrotra, Francisco Gutierrez, Kyle Smith, Gloria Seo, Austin Garcia, Bryan Chin, Marty Kandes, and Mary P Thomas. 2024. Preliminary Results of the MLPerf BERT Inference Benchmark on AMD Instinct GPUs. In Practice and Experience in Advanced Research Computing 2024: Human Powered Computing (PEARC '24). Association for Computing Machinery, New York, NY, USA, Article 59, 1 to 5. https://doi.org/10.1145/3626203.3670589
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S. Mehringer, M. P. Thomas, K. Cahill, D. Joiner, R. Knepper, and J. H. Powell, Scaling HPC Education, in Tenth SC Workshop on Best Practices for HPC Training and Education BPHTE23, 2023, pp. 1 to 6
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M. P. Thomas, A. W. Goetz, M. C. Kandes, and R. S. Sinkovits, Developing a Best Practices Training Program in Cyberinfrastructure-Enabled Machine Learning Research, PEARC 2023 Conf. Ser. Pract. Exp. Adv. Res. Comput., pp. 390 to 394, 2023
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A. Govind, Y. Jing, Matthew Mikhailov, M. P. Thomas, et. al., SCC22 Reproducibility Challenge : Productivity , Portability , Performance : Data-Centric Python, Accepted, IEEE Trans. Parallel Distrib. Syst., 2023.
For a list of other/selected publications, check here.
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