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DOE OSTI · 2311418

Equation-based and data-driven modeling: Open-source software current state and future directions

Gunnell, LaGrande·Nicholson, Bethany L.·Hedengren, John D.
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Abstract

Here, a review of current trends in scientific computing reveals a broad shift to open-source and higher-level programming languages such as Python and growing career opportunities over the next decade. Open-source modeling tools accelerate innovation in equation-based and data-driven applications. Significant resources have been deployed to develop data-driven tools (PyTorch, TensorFlow, Scikit-learn) from tech companies that rely on machine learning services to meet business needs while keeping the foundational tools open. Open-source equation-based tools such as Pyomo, CasADi, Gekko, and JuMP are also gaining momentum according to user community and development pace metrics. Integration of data-driven and principles-based tools is emerging. New compute hardware, productivity software, and training resources have the potential to radically accelerate progress. However, long-term support mechanisms are still necessary to sustain the momentum and maintenance of critical foundational packages.

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Gunnell, LaGrande, Nicholson, Bethany L., Hedengren, John D.. 2023-11-28. Equation-based and data-driven modeling: Open-source software current state and future directions. https://doi.org/10.1016/j.compchemeng.2023.108521

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