{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/pressio-enabling-projection-based-model","title":"Pressio: Enabling projection-based model reduction for large-scale nonlinear dynamical systems","arxiv_id":"2003.07798","date":"2020-03-17","proceeding":null,"authors":["Francesco Rizzi","Patrick J. Blonigan","Eric J. Parish","Kevin T. Carlberg"],"abstract":"This work introduces Pressio, an open-source project aimed at enabling leading-edge projection-based reduced order models (ROMs) for large-scale nonlinear dynamical systems in science and engineering. Pressio provides model-reduction methods that can reduce both the number of spatial and temporal degrees of freedom for any dynamical system expressible as a system of parameterized ordinary differential equations (ODEs). We leverage this simple, expressive mathematical framework as a pivotal design choice to enable a minimal application programming interface (API) that is natural to dynamical systems. The core component of Pressio is a C++11 header-only library that leverages generic programming to support applications with arbitrary data types and arbitrarily complex programming models. This is complemented with Python bindings to expose these C++ functionalities to Python users with negligible overhead and no user-required binding code. We discuss the distinguishing characteristics of Pressio relative to existing model-reduction libraries, outline its key design features, describe how the user interacts with it, and present two test cases -- including one with over 20 million degrees of freedom -- that highlight the performance results of Pressio and illustrate the breath of problems that can be addressed with it.","url_abs":"https://arxiv.org/abs/2003.07798v3","url_pdf":"https://arxiv.org/pdf/2003.07798v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"pressio-enabling-projection-based-model","repo_url":"https://github.com/Pressio/pressio","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"pressio-enabling-projection-based-model","repo_url":"https://github.com/Pressio/pressio4py","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"pressio-enabling-projection-based-model","repo_url":"https://github.com/Pressio/pressio-tutorials","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}