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AgileOS: A GPU Operating System Layer for Protected CUDA Services

arXiv Security Archived Jun 08, 2026 ✓ Full text saved

arXiv:2606.06697v1 Announce Type: new Abstract: Modern GPU applications increasingly interact with storage systems, network devices, vendor libraries, and GPU-resident services rather than executing only isolated compute kernels. This shift creates a need for operating-system-like protection around GPU services, where service metadata, device queues, memory-mapped I/O regions, and library-internal state should not be directly exposed to untrusted application kernels. However, today's CUDA progra

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    Computer Science > Cryptography and Security [Submitted on 4 Jun 2026] AgileOS: A GPU Operating System Layer for Protected CUDA Services Zhuoping Yang, Yiyu Shi, Alex Jones, Peipei Zhou Modern GPU applications increasingly interact with storage systems, network devices, vendor libraries, and GPU-resident services rather than executing only isolated compute kernels. This shift creates a need for operating-system-like protection around GPU services, where service metadata, device queues, memory-mapped I/O regions, and library-internal state should not be directly exposed to untrusted application kernels. However, today's CUDA programming model, by default, still gives each application direct ownership of its CUDA context, device pointers, runtime handles, module loading path, and kernel launches, leaving protected GPU services to build their own ad hoc interfaces and isolation mechanisms. This paper presents the initial design and prototype scope of AgileOS, a GPU operating-system layer for protected CUDA services. AgileOS virtualizes CUDA at the library boundary: applications link against client-side CUDA Runtime, Driver, and selected library shims, while a trusted runtime worker owns the real CUDA context and mediates supported operations. To protect service state and module interfaces, AgileOS also defines a GPU memory-management model that separates user allocations from protected module/MMIO ranges, using pointer validation and memory access guards via PTX injection. AgileOS is modularized and flexible, supporting a range of protected services and existing libraries such as cuFFT and PyTorch. The prototype includes client-side interceptors, worker-side CUDA handlers, virtualized CUDA object tables, protected AgileOS modules, a GPU memory manager that separates user allocations from protected module/MMIO ranges, selected trusted library adapters, and the PTX-level kernel memory guard. Subjects: Cryptography and Security (cs.CR); Operating Systems (cs.OS) Cite as: arXiv:2606.06697 [cs.CR]   (or arXiv:2606.06697v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2606.06697 Focus to learn more Submission history From: Zhuoping Yang [view email] [v1] Thu, 4 Jun 2026 20:34:56 UTC (305 KB) Access Paper: HTML (experimental) view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-06 Change to browse by: cs cs.OS References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation 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 Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
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    arXiv Security
    Category
    ◬ AI & Machine Learning
    Published
    Jun 08, 2026
    Archived
    Jun 08, 2026
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