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A survey of software implementations used by application codes in the Exascale Computing Project., , , , , , , and . Int. J. High Perform. Comput. Appl., 36 (1): 5-12 (2022)Machine Learning-Powered Mitigation Policy Optimization in Epidemiological Models., , , , , and . Healthcare AI and COVID-19 Workshop, volume 184 of Proceedings of Machine Learning Research, page 63-72. PMLR, (2022)The basic matrix library (BML) for quantum chemistry., , , , , , , , and . J. Supercomput., 74 (11): 6201-6219 (2018)Performance Portability in the Exascale Computing Project: Exploration Through a Panel Series., , , , , , and . Comput. Sci. Eng., 23 (5): 46-54 (2021)Recent advances in large-scale atomistic materials simulations., and . Comput. Sci. Eng., 1 (2): 10-11 (1999)Modeling targeted layered containment of an influenza pandemic in the United States, , , , , , , , , and 7 other author(s). Proceedings of the National Academy of Sciences, 105 (12): 4639-4644 (January 2008)Distributed Database Kriging for Adaptive Sampling (D2KAS)., , , , , , and . Comput. Phys. Commun., (2015)Extending the time scale in atomistic simulation of materials, , and . Annu. Rev. Mat. Res., (2002)Database assisted distribution to improve fault tolerance for multiphysics applications., , , and . Co-HPC@SC, page 4:1-4:8. ACM, (2015)Accurate Calibration of Agent-based Epidemiological Models with Neural Network Surrogates., , , , , and . CoRR, (2020)