About the Conference
Computational Science and Engineering (CSE) brings together engineering, applied mathematics, and computer science to form powerful simulation tools for model-based development, design, decision support and diagnostics. Herein, methodological and application-focused research in CSE acts as a driver for innovation in all fields of science and engineering. Yet often, aspects of sustainability are not systematically and holistically considered.
Sustainability is quite generally referred to as the avoidance of the depletion of (natural) resources in order to maintain an ecological balance. It remains a fuzzy concept that considers many questions, like environmental impact and conservation, economic aspects, resilience and fairness. In the past decade it became clear that sustainability affects literally any human activities, including a vast range of research questions.
Theme: Computing for Sustainability
Ever since methods and tools of CSE have been used to optimize product design and processes, yet multi-disciplinary design, analysis and optimization (MDAO) still constitute one of the major challenges in model-based engineering. Integrating a sustainability dimension in terms of minimizing the product’s or processes’ anticipated consumption of energy and other natural resources, or in terms of fostering the product’s feasibility for circular economy and up-cycling, adds new, multifold constraints and optimization targets to complex CSE workflows. Modern concepts of CSE tailored to seamlessly simulate processes across scales, while powerful enough to optimize across large search spaces will pave the way for a new era of product design based on smart digital twins and multi-disciplinary design optimization.
Making progress in this field calls for a concerted effort to increase our ability for complexity management in application-oriented utilization of CSE methods. We further need push methodological innovation on high-dimensional optimization and multiscale and complex geometry CSE methods towards efficient and reliable utilization of modern CSE for the development of sustainable technologies with potential to solve societal challenges, such as low carbon footprint technologies, low-cost technological renewable energy solutions, and intelligent predictive maintenance and circular economy strategies.
Theme: Sustainable Computing
The environmental impact of computing itself is being investigated under the keyword of . The goals are to reduce the environmental impact and maximize energy efficiency during any type of computing. Eventually, the goal is to come up with the best trade off between energy consumption and knowledge return, and to increase the recyclability of data and simulation. Energy efficient, green computing is important for all classes of computational systems, ranging from handheld systems to large-scale data centers.
Within CSE research the efficiency of algorithms plays a major role. It affects the amount of computer resources required for any given computing function and there are many efficiency trade-offs in writing programs. Algorithms can be selected according to their resource consumption, such as switching from a slow (e.g. linear) search algorithm to a fast (e.g. hashed or indexed) search algorithm. Within high-performance computing the Green500-list is a biannual ranking of supercomputers, from the top-500 list of supercomputers, in terms of energy efficiency measuring performance per watt.
Sustainability and impact have gained renewed interest in the context of machine learning where the training of deep artificial neural networks consume vast amounts of energy resources. This concern increased even more with the arrival of large language models and GPT-based chat-bots, where the actual chat usage requires enormous compute resources to provide a life-like interaction. This also puts the sustainable usage of machine learning in CSE into question.
Theme: Sustainable Software
Much of the future research impact of CSE will rely on the sustainable development, consequent integration, and creative utilization of high-level research software. The importance of reliable, re-usable, and composable software will even grow further, and proficiency in initiating, deploying, and continuously developing open research software will be a key asset across all applied science and engineering domains. A sustainable and effective approach to research software engineering (RSE) is, therefore, not only of central importance to CSE research, but likewise an important future topic at the institutional level for all academic institutions. Research software is the result of a significant resource investment. It is, what helps turning an idea into impactful innovation and generates knowledge from a hypotheses. Software integrates scientific outcomes of interdisciplinary research efforts and often lays the foundation for cross-institutional collaborations.
RSE methods that foster seamlessly re-usable, high-quality software in times of hyperproductivity are hence necessary for impact maximization and call for focused RSE strategies.