RAMSES: Secure high-performance computing for sensitive data

Computer Science > Distributed, Parallel, and Cluster Computing [Submitted on 26 Jun 2026] RAMSES: Secure high-performance computing for sensitive data Peter Heger, Lech Nieroda, Roland Pabel, Christoph Stollwerk, Stefan Borowski, Kamil Tokmakov, Michael Commer, Martin Peifer, Stefan Wesner, Viktor Achter Traditionally, the architecture of high-performance computing (HPC) systems is tailored for speed, while highly secure computer systems must sacrifice speed for security. However, a wide range of scientific domains, such as the life sciences, call for a combination of performance and security to allow processing sensitive data at scale. Here, we present RAMSES (Research Accelerator for Modeling and Simulation with Enhanced Security), an HPC system designed from the ground up to deliver high performance within a robust security framework. RAMSES integrates hardware-based memory encryption of AMD processors with state-of-the-art file encryption from IBM Storage Scale and the Thales CipherTrust manager, establishing an HPC platform that ensures continuous encryption throughout the data life cycle - at rest, in transit, and in use - in compliance with major data protection standards (European General Data Protection Regulation, ISO/IEC 27001 certification, and Federal Information Processing Standards). In addition, we implemented advanced operating system hardening, a multi-layered security architecture, and mandatory multi-factor authentication to adapt the HPC environment to increased security demands. Benchmark results from the biomedical sector demonstrate that the performance impact of the secure environment is limited and that integration of the conflicting requirements speed and security can be achieved while preserving a coherent, flexible, and user-friendly system. Comments: 27 pages, 5 figures, 2 tables Subjects: Distributed, Parallel, and Cluster Computing (cs.DC); Cryptography and Security (cs.CR) Cite as: arXiv:2606.27919 [cs.DC]   (or arXiv:2606.27919v1 [cs.DC] for this version)   https://doi.org/10.48550/arXiv.2606.27919 Focus to learn more Submission history From: Peter Heger [view email] [v1] Fri, 26 Jun 2026 10:10:27 UTC (1,381 KB) Access Paper: HTML (experimental) view license Current browse context: cs.DC < prev   |   next > new | recent | 2026-06 Change to browse by: cs cs.CR 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?)