The benefits and challenges of explicit memory management in OpenMP Target GPU offloading

[2608.14554] The benefits and challenges of explicit memory management in OpenMP Target GPU offloading Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Computer Science > Distributed, Parallel, and Cluster Computing arXiv:2608.14554 (cs) [Submitted on 11 May 2026] Title: The benefits and challenges of explicit memory management in OpenMP Target GPU offloading Authors: Igor Sfiligoi View a PDF of the paper titled The benefits and challenges of explicit memory management in OpenMP Target GPU offloading, by Igor Sfiligoi View PDF Abstract: OpenMP Target Offload is a popular GPU technology for porting compute codes that operate on large buffers. One of the main usability features that is typically emphasized is the semi-automatic handling of buffer synchronization in partitioned memory setups, typical of discreet GPU systems. That feature however comes with potential correctness, performance and resource consumption drawbacks. This paper outlines the drawbacks of that approach and outlines how explicit handling of buffer locality, natively supported through OpenMP, avoids most of those pitfalls, but also comes with its own downsides. Comments: 4 pages Subjects: Distributed, Parallel, and Cluster Computing (cs.DC) Cite as: arXiv:2608.14554 [cs.DC] (or arXiv:2608.14554v1 [cs.DC] for this version) https://doi.org/10.48550/arXiv.2608.14554 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Igor Sfiligoi [ view email ] [v1] Mon, 11 May 2026 20:52:02 UTC (225 KB) Full-text links: Access Paper: View a PDF of the paper titled The benefits and challenges of explicit memory management in OpenMP Target GPU offloading, by Igor Sfiligoi View PDF view license Current browse context: cs.DC < prev | next > new | recent | 2026-08 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs . Which authors of this paper are endorsers? | Disable MathJax ( What is MathJax? ) We gratefully acknowledge support from our major funders , member institutions , , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab) Major funding support from

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