{"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/pysph-a-python-based-framework-for-smoothed","title":"PySPH: a Python-based framework for smoothed particle hydrodynamics","arxiv_id":"1909.04504","date":"2019-09-10","proceeding":null,"authors":["Prabhu Ramachandran","Aditya Bhosale","Kunal Puri","Pawan Negi","Abhinav Muta","A Dinesh","Dileep Menon","Rahul Govind","Suraj Sanka","Amal S Sebastian","Ananyo Sen","Rohan Kaushik","Anshuman Kumar","Vikas Kurapati","Mrinalgouda Patil","Deep Tavker","Pankaj Pandey","Chandrashekhar Kaushik","Arkopal Dutt","Arpit Agarwal"],"abstract":"PySPH is an open-source, Python-based, framework for particle methods in general and Smoothed Particle Hydrodynamics (SPH) in particular. PySPH allows a user to define a complete SPH simulation using pure Python. High-performance code is generated from this high-level Python code and executed on either multiple cores, or on GPUs, seamlessly. It also supports distributed execution using MPI. PySPH supports a wide variety of SPH schemes and formulations. These include, incompressible and compressible fluid flow, elastic dynamics, rigid body dynamics, shallow water equations, and other problems. PySPH supports a variety of boundary conditions including mirror, periodic, solid wall, and inlet/outlet boundary conditions. The package is written to facilitate reuse and reproducibility. This paper discusses the overall design of PySPH and demonstrates many of its features. Several example results are shown to demonstrate the range of features that PySPH provides.","url_abs":"https://arxiv.org/abs/1909.04504v3","url_pdf":"https://arxiv.org/pdf/1909.04504v3.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":"pysph-a-python-based-framework-for-smoothed","repo_url":"https://github.com/pypr/pysph","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"pysph-a-python-based-framework-for-smoothed","repo_url":"https://github.com/chrisnbattista/how-to-swarm-cloud","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1909.04504","atlas_url":"https://app.syntology.ai/?focus=1909.04504","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1909.04504"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-25T09:33:49+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. 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