AI 中文总结
该研究针对随机材料的风险规避优化问题，开发了采用熵风险测度的算法及兼容的采样技术，探索了利用现代异构硬件加速求解三维偏微分方程的方法，取得了算法与硬件利用的进展。
AI 中文摘要
我们总结了随机材料中风险规避优化问题在算法开发与硬件利用方面的进展，包括采用熵风险测度的风险规避优化，以及与优化框架兼容的最新随机材料采样技术。此外，我们还探讨了利用现代异构硬件架构高效求解三维偏微分方程的最新进展。
英文摘要
We summarize our advances in the algorithmic development and hardware utilization for risk-averse optimization problems in random materials. This includes risk-averse optimization using the entropic risk measure, as well as recently developed sampling techniques for random materials, that are interoperable with the optimization framework. Furthermore, we discuss recent progress in the efficient utilization of modern hybrid hardware architectures for these methods to solve three-dimensional partial differential equations.
