Hardware-Software Codesign Optimization for Scientific and Industrial Systems

This paper addresses the critical issue of hardware-software co-design in complex systems, drawing parallels between scientific experiments and industrial applications. The core argument is that optimizing these systems requires considering the inter-relation between hardware parameters (data production) and software parameters (data analysis). The authors highlight that neglecting this coupling can lead to suboptimal performance. The paper explores use cases from particle physics and industry, emphasizing the potential for co-design procedures to identify the global maximum of relevant utility functions. The research suggests numerous opportunities to advance methods and tools for hardware-software co-design optimization, bridging fundamental science and industry through application- and challenge-driven projects. This approach could shape the future of scientific experiments and industrial systems by enabling more efficient and effective data production and analysis. The paper advocates for a holistic approach to system design, recognizing the importance of considering all components and their interactions.

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