{"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/scida-scalable-analysis-for-scientific-big","title":"scida: scalable analysis for scientific big data","arxiv_id":"2402.17818","date":"2024-02-27","proceeding":null,"authors":["Chris Byrohl","Dylan Nelson"],"abstract":"scida is a Python package for reading and analyzing large scientific data sets with support for various cosmological and galaxy formation simulations out-of-the-box. Data access is provided through a hierarchical dictionary-like data structure after a simple load() function. Using the dask library for scalable, parallel and out-of-core computation, all computation requests from a user session are first collected in a task graph. Arbitrary custom analysis, as well as all available dask (array) operations, can be performed. The subsequent computation is executed only upon request, on a target resource (e.g. a HPC cluster).","url_abs":"https://arxiv.org/abs/2402.17818v1","url_pdf":"https://arxiv.org/pdf/2402.17818v1.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":"scida-scalable-analysis-for-scientific-big","repo_url":"https://github.com/cbyrohl/scida","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"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}