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Building Trust in Earth Science Findings through Data Traceability and Results Explainability.

, , , , , , and . IEEE Trans. Parallel Distributed Syst., 34 (2): 704-717 (February 2023)

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AI4IO: A suite of AI-based tools for IO-aware scheduling., , , and . Int. J. High Perform. Comput. Appl., 36 (3): 370-387 (2022)Orchestration of materials science workflows for heterogeneous resources at large scale., , , , , , , , , and . Int. J. High Perform. Comput. Appl., 37 (3-4): 260-271 (July 2023)On the Power of Combiner Optimizations in MapReduce Over MPI Workflows., , , , , , and . ICPADS, page 441-448. IEEE, (2018)Building Trust in Earth Science Findings through Data Traceability and Results Explainability., , , , , , and . IEEE Trans. Parallel Distributed Syst., 34 (2): 704-717 (February 2023)VPIC 2.0: Next Generation Particle-in-Cell Simulations., , , , , and . IEEE Trans. Parallel Distributed Syst., 33 (4): 952-963 (2022)A lightweight method for evaluating in situ workflow efficiency., , , , , , , , and . J. Comput. Sci., (2021)Recognition of Outstanding Future Generation Computer Systems Reviewers for 2022.. Future Gener. Comput. Syst., (June 2023)Flux: Overcoming scheduling challenges for exascale workflows., , , , , , , , , and 2 other author(s). Future Gener. Comput. Syst., (2020)Building Containerized Environments for Reproducibility and Traceability of Scientific Workflows., , and . CoRR, (2020)EduHPC Lightning Talk Summary., , , , , , , , , and 7 other author(s). SC Workshops, page 374-378. ACM, (2023)