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平均每年 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。南极冰盖的冰排放量增加对海平面上升有重大贡献。然而，其对气候变化的动态反应仍然是海平面上升预测的根本不确定性。传统的中央处理单元（CPU）限制了运行南极洲大陆尺度模拟集合所需的时间，以更好地评估其海平面对气候强迫参数化不确定性的敏感度。就计算机内存和执行时间而言，冰流预测是冰盖模拟中计算成本最高的部分。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，可以增强速度和预测性能之间的平衡。在这项奖学金的支持下，首席研究员和一名研究生将研究上述内容，以便及时运行南极洲大陆尺度的三维（3-D）高空间分辨率高阶模拟集合，以更好地评估其海平面对气候强迫参数化不确定性的敏感度，这在以前是不可能的。该研究基础设施改进 Track-4 EPSCoR 研究员 (RII Track-4) 项目将为北达科他大学的高级讲师提供奖学金并为研究生提供培训。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，并且空间分辨率等于或大于接地线附近的 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且无矩阵的方法，并结合 GPU 及时运行大陆尺度南极洲 3D 高空间分辨率高阶模拟集合的能力，以更好地评估其海平面对气候强迫参数化不确定性的敏感度，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，因此迫切需要它们，并将在未来几十年内极大地有益于过程导向和海平面预测研究。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，更好地识别对预测中的不确定性负有最大责任的来源，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，所开发的方法和软件可以扩展以加速其他大规模纳维-斯托克斯或不可压缩流体流动应用。该奖项反映了 NSF 的法定使命，并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，被认为值得支持。