{"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/enumerating-hardware-software-splits-with","title":"Enumerating Hardware-Software Splits with Program Rewriting","arxiv_id":"2003.00290","date":"2020-02-29","proceeding":null,"authors":["Gus Smith","Zachary Tatlock","Luis Ceze"],"abstract":"A core problem in hardware-software codesign is in the sheer size of the design space. Without a set ISA to constrain the hardware-software interface, the design space explodes. This work presents a strategy for managing the massive hardware-software design space within the domain of machine learning inference workloads and accelerators. We first propose EngineIR, a new language for representing machine learning hardware and software in a single program. Then, using equality graphs -- a data structure from the compilers literature -- we suggest a method for efficiently enumerating the design space by performing rewrites over our representation.","url_abs":"http://arxiv.org/abs/2003.00290v1","url_pdf":"http://arxiv.org/pdf/2003.00290v1.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":"enumerating-hardware-software-splits-with","repo_url":"https://github.com/gussmith23/glenside","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}