{"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/high-performance-simultaneous-multiprocessing","title":"High-Performance Simultaneous Multiprocessing for Heterogeneous System-on-Chip","arxiv_id":"2008.08883","date":"2020-08-20","proceeding":null,"authors":["Kris Nikov","Mohammad Hosseinabady","Rafael Asenjo","Andrés Rodríguezz","Angeles Navarro","Jose Nunez-Yanez"],"abstract":"This paper presents a methodology for simultaneous heterogeneous computing, named ENEAC, where a quad core ARM Cortex-A53 CPU works in tandem with a preprogrammed on-board FPGA accelerator. A heterogeneous scheduler distributes the tasks optimally among all the resources and all compute units run asynchronously, which allows for improved performance for irregular workloads. ENEAC achieves up to 17\\% performance improvement \\ignore{and 14\\% energy usage reduction,} when using all platform resources compared to just using the FPGA accelerators and up to 865\\% performance increase \\ignore{and up to 89\\% energy usage decrease} when using just the CPU. The workflow uses existing commercial tools and C/C++ as a single programming language for both accelerator design and CPU programming for improved productivity and ease of verification.","url_abs":"https://arxiv.org/abs/2008.08883v1","url_pdf":"https://arxiv.org/pdf/2008.08883v1.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":"high-performance-simultaneous-multiprocessing","repo_url":"https://github.com/kranik/ENEAC","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}