CDI-Type I: Small Resources Supercomputing: High Performance Computing in the Earth Sciences

在生态学、海洋学和气候科学等不同领域，有大量关于数值模拟的科学工作来模拟物理过程，如平流和扩散。不幸的是，解决这些过程的小时间和空间尺度特征的计算代价很高，而且往往将基础研究限制在短时间和小区域。此外，由于这些小尺度过程可能导致区域和全球尺度上的涌现特性，这种有限范围(无论是在空间上还是在时间上)的模拟可能会导致对大尺度动力学的错误理解。在气候科学领域尤其如此。在这项工作中，我们建议将一个用户友好的高性能计算框架引入到桌面计算环境中，以便可以在大范围内模拟小规模的过程，并了解可伸缩的真实本质。特别是，这项工作将利用多处理器图形处理单元(GPU)将计算模拟的速度比传统的工作站处理器提高高达三个数量级。这些多处理器GPU提供了一种以这样一种方式来分配图形渲染负载的方式，即，例如，最先进的计算机游戏在视觉上是逼真的，并且速度足够快以允许用户交互。此外，这些允许快速图形渲染的相同图形处理器也可以用于显著加速数值模拟。然而，尽管有个别团队利用了GPU技术，但总的来说，大多数科学家还没有。因此，这项工作的一个目标是开发用于GPU模拟的软件工具，这些工具既足够灵活，可以在一系列科学问题上使用，而且对于没有GPU编程经验的研究人员来说很容易使用。该项目将为基于网格的偏微分方程模拟和基于粒子的模拟提供模拟工具。虽然这项工作的技术目标是将高性能计算引入桌面计算环境，但它将在追求与气候变化相关的科学问题时这样做。这项研究的调查人员在北极和大沼泽地拥有丰富的专业知识，因此将专注于与这些地区相关的问题。科学目标是：(I)更好地了解过程是如何扩展的。具体地说，小规模的非线性和反馈是否会导致规模上的涌现特性。(2)在北极，目标是从机制上理解雪和灌木如何独立和相互作用地影响对北极冻土带土壤氮素动态和分解的物理和生物控制，以及这些动态又如何影响植被组成和生产力。(Iii)在大沼泽地，目标是确定支配山脊和崩塌植被系统形成和维持的动态，并了解海平面和咸水入侵的管理情景和变化如何改变这种有模式的植被系统的形式和功能。湿地植被、营养盐和水运动相互作用的调查和发现，可以为该地区的土地利用和资源管理提供指导。积雪捕获模型可以更好地了解气候变化和北极植被之间的相互作用。最后，基于网格的模拟和基于粒子的模拟的工具可以为在许多其他科学调查领域使用配备GPU的台式计算机提供平台。

There is a large body of scientific work on numerical simulation to model physical processes such as advection and diffusion in disparate fields such as ecology, oceanography, and climate science. Unfortunately, resolving the small time and spatial scale characteristics of these processes is computationally expensive and often limits fundamental studies to short times and small areas. Moreover, as these small-scale processes may lead to emergent properties on the regional and global scales, such simulations of limited scope (either in space or time) may lead to an incorrect understanding of large-scale dynamics. This is especially true in the climate sciences. In this work we propose to bring a user-friendly framework for High Performance Computing to the desktop computing environment so that small-scale processes can be simulated over large areas and the true nature of scaling understood. In particular, this work will take advantage of multi-processor Graphics Processing Units (GPUs) to increase the speed of computational simulations by up to three orders of magnitude over conventional workstation processors. These multi-processor GPUs provide a way to distribute the graphics rendering loads in such a way that, for example, state of the art computer games are visually realistic and fast enough to allow for user interactivity. Moreover, these same GPUs that permit fast graphics rendering can also be used to significantly accelerate numerical simulations. However, while there are individual groups that have taken advantage of GPU technology, by and large most scientists have not. Thus one goal of this work is to develop software tools for GPU simulation that are both flexible enough to use across a range of scientific problems, and are easy to use for researchers who have no GPU programming experience. This project will provide simulation tools for grid-based simulations for partial differential equations and particle-based simulations.While the technical objective of this work is to bring High Performance Computing to the desktop computing environment, it will be done so in the pursuit of scientific questions related to climate change. The investigators of this study have a history of expertise in the Arctic and the Everglades, and therefore will focus on problems relevant to these areas. The scientific goals are: (i) To better understand how processes scale. Specifically, whether small-scale non-linearities and feedbacks lead to emergent properties at scale. (ii) In the Arctic, the goal is to develop a mechanistic understanding of how snow and shrubs independently and interactively affect physical and biological controls over soil nitrogen dynamics and decomposition in arctic tundra, and how these dynamics in turn affect vegetation composition and productivity. (iii) In the Everglades, the goal is identify the dynamics that govern the formation and maintenance of the ridge and slough vegetation system and understand how management scenarios and changes in sea level and salt water intrusion will alter form and function of this patterned vegetation system.This research has the potential for broader impact in several areas. The investigations and discoveries about the interaction between vegetation, nutrients and water motion in the Everglades may provide guidance in terms of land use and resource management in this region. The snow capture models could provide a better understanding about the interaction between climate change and vegetation in the Arctic. Finally, the tools for grid-based simulations and particle-based simulations can provide a platform for using desktop computers with GPUs in a number of other areas of scientific investigation.