2025/10/17 by Tim Kraus, Kraus, Tim, Axel Sauer +3
Computer Science · Decision Sciences · #Cloud Computing and Resource Management #Distributed #FOS: Computer and information sciences #Parallel #Security and Verification in Computing #Simulation Techniques and Applications #and Cluster Computing (cs.DC)
paper · pdf · doi:10.48550/arxiv.2510.15355
openalex publication_date 2025/10/17 · openalex created_date 2025/10/21 · openalex updated_date 2026/07/28
The rapid evolution of embedded systems, along with the growing variety and complexity of AI algorithms, necessitates a powerful hardware/software co-design methodology based on virtual prototyping technologies. The market offers a diverse range of simulation solutions, each with its unique technological approach and therefore strengths and weaknesses. Additionally, with the increasing availability of remote on-demand computing resources and their adaptation throughout the industry, the choice of the host infrastructure for execution opens even more new possibilities for operational strategies. This work explores the dichotomy between local and cloud-based simulation environments, focusing on the trade-offs between scalability and privacy. We discuss how the setup of the compute infrastructure impacts the performance of the execution and security of data involved in the process. Furthermore, we highlight the development workflow associated with embedded AI and the critical role of efficient simulations in optimizing these algorithms. With the proposed solution, we aim to sustainably improve trust in remote simulations and facilitate the adoption of virtual prototyping practices.