RII Track-4:NSF: Continental-scale, high-order, high-spatial-resolution, ice flow modeling based on graphics processing units (GPUs)

RII Track-4：NSF：基于图形处理单元 (GPU) 的大陆尺度、高阶、高空间分辨率冰流建模

• 批准号: 2327095
• 负责人: Anjali Sandip
• 金额: $ 28.61万
• 依托单位: University of North Dakota Main Campus
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-01-15 至 2025-12-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2327095&HistoricalAwards=false
• 关键词: RII; Track; NSF; Continental; scale

The global mean sea level is rising at an average rate of 3.7 mm yr−1, posing a significant threat to coastal communities and global ecosystems. The increase in ice discharge from the Antarctic ice sheet contributes significantly to the rising sea levels. However, its dynamic response to climate change remains a fundamental uncertainty in sea level rise projections. Conventional central processing units (CPUs) limit the time needed to run simulation ensembles of continental-scale Antarctica forward in time to assess better its sea-level contribution sensitivity to uncertainties in climate forcing parameterization. Ice flow predictions are the most computationally expensive part of ice sheet simulations in terms of computer memory and execution time. Leveraging graphics processing units (GPUs) to alleviate the high computational costs associated with ice flow simulations can provide an enhanced balance between speed and predictive performance. With the support of this fellowship, the PI and a graduate student will investigate those mentioned above to run three-dimensional (3-D) high-spatial-resolution higher-order simulation ensembles of continental-scale Antarctica forward in time to assess better its sea-level contribution sensitivity to uncertainties in climate forcing parameterization, which has been previously impossible. This Research Infrastructure Improvement Track-4 EPSCoR Research Fellows (RII Track-4) project will provide a fellowship to a Senior Lecturer and training for a graduate student at the University of North Dakota. This work would be conducted in collaboration with researchers at Dartmouth College.Several recent studies have used stress balance models with complexities lower than the 3-D Blatter-Pattyn higher-order model and spatial resolutions equal to or greater than 1 km near grounding lines to keep computational resources manageable when running simulation ensembles forward in time at the continental scale. These studies partially assess the Antarctic sea-level contribution sensitivity to uncertainties in climate forcing parameterization. The study will explicitly test an accelerated and matrix-free method in conjunction with the GPU’s ability to run 3-D high-spatial-resolution higher-order simulation ensembles of continental-scale Antarctica forward in time to assess better its sea level contribution sensitivity to uncertainties in climate forcing parameterization, which has been previously impossible. These findings have not been available due to computational costs; however, they are urgently needed as the Antarctic Ice Sheet loses mass at an increasing rate and will significantly benefit process-oriented and sea-level-projection studies over the coming decades. The methods developed will enable the ice sheet community to quantify the uncertainty bounds in projections with increased confidence, better identify the sources most responsible for the uncertainties in projections, and determine the types of satellite measurements that must be made to reduce uncertainty in projections. Furthermore, the methods and software developed can be extended to accelerate other large-scale Navier-Stokes or incompressible fluid flow applications.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

全球平均海平面正以每年3.7毫米的速度上升，对沿海社区和全球生态系统构成重大威胁。南极冰盖冰流量的增加是海平面上升的重要原因。然而，它对气候变化的动态反应仍然是海平面上升预测的一个基本不确定因素。传统的中央处理器（CPU）限制了在时间上向前运行大陆尺度南极洲的模拟集合所需的时间，以更好地评估其海平面贡献对气候强迫参数化中的不确定性的敏感性。冰流预测是冰盖模拟计算中最昂贵的部分，在计算机内存和执行时间方面。利用图形处理单元（GPU）来减轻与冰流模拟相关的高计算成本可以在速度和预测性能之间提供增强的平衡。在该奖学金的支持下，PI和一名研究生将调查上述内容，以便及时运行大陆尺度南极洲的三维（3-D）高空间分辨率高阶模拟集合，以更好地评估其海平面贡献对气候强迫参数化不确定性的敏感性，这在以前是不可能的。这个研究基础设施改善轨道-4 EPSCoR研究员（RII轨道-4）项目将提供奖学金的高级讲师和培训的研究生在北达科他州的大学。这项工作将与达特茅斯学院的研究人员合作进行，最近的几项研究使用了复杂性低于3-D Blatter-Pattyn高阶模型的应力平衡模型，在接地线附近的空间分辨率等于或大于1公里，以便在大陆尺度上及时运行模拟集合时保持计算资源的可管理性。这些研究部分评估了南极海平面对气候强迫参数化不确定性的敏感性。该研究将明确测试一种加速和无矩阵方法，并结合GPU的能力，及时运行大陆尺度南极洲的3-D高空间分辨率高阶模拟集合，以更好地评估其海平面贡献对气候强迫参数化不确定性的敏感性，这在以前是不可能的。由于计算成本的原因，这些研究结果尚未公布;然而，由于南极冰盖的质量损失速度越来越快，迫切需要这些研究结果，并将在未来几十年内大大有利于以过程为导向的海平面预测研究。所开发的方法将使冰盖界能够以更高的置信度量化预测中的不确定性界限，更好地查明造成预测中不确定性的最主要来源，并确定为减少预测中的不确定性而必须进行的卫星测量类型。此外，开发的方法和软件可以扩展到加速其他大型Navier-Stokes或不可压缩流体流的应用。该奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。