High performance computing framework for GCM-driven climate change simulation with the routing model WATROUTE

使用路由模型 WTROUTE 进行 GCM 驱动的气候变化模拟的高性能计算框架

• 批准号: 508025-2017
• 负责人: Henry, Christopher
• 金额: $ 0.91万
• 依托单位: University of Winnipeg
• 依托单位国家: 加拿大
• 项目类别: Engage Plus Grants Program
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=640678
• 关键词: performance; computing; framework; GCM; driven

Manitoba Hydro's resource planning process is influenced by a variety of factors including water supply andelectrical energy demand. As a result, understanding the sensitivity of planning decisions to future streamflowscenarios are important to their integrated resource planning process. Streamflow scenarios can be developedby combining global climate model simulated runoff values with the WATROUTE routing model for theNelson-Churchill Watershed. The routing model is implemented in WATROUTE, the routing component ofthe Canadian Hydrological Model (CHARM) suite of programs. Further, WATROUTE is the computationalbottleneck for the streamflow simulation processes, incurring long runtimes, especially when projecting manyyears into the future. Thus, finding ways of significantly reducing the runtime of WATROUTE is of greatimportance to Manitoba Hydro. Moreover, the parallel nature of the routing model is an ideal fit for executionon the massively parallel processors inherent in graphics processing units (GPUs), which have recently becomeavailable for general-purpose scientific computing. This work is an extension of the results from an EngageGrant with Manitoba Hydro, where the aim was to create a highly-parallel, GPU-based,high-performance-computing implementation of the WATROUTE routing model to assist Manitoba Hydro'sresource planning process. Tremendous progress was achieved toward this aim through significant reduction inthe routing model runtime. As a result, the aim of this Engage Plus Grant is to pursue the reduction ofWATROUTE's overall runtime using GPUs, produce a release ready version of WATROUTE, explore theapplication of WATROUTE to datasets previously too large to process, and investigate the use ofWATROUTE on systems with multiple GPUs. Benefits realized by this work may also have a positive impacton the MEC-Surface and Hydrology System (MESH) and the Canadian Regional Climate Model, as both useWATROUTE.

马尼托巴水电的资源规划过程受到各种因素的影响，包括水供应和电能需求。因此，了解规划决策对未来径流情景的敏感性对他们的综合资源规划过程非常重要。通过将全球气候模型模拟的径流值与纳尔逊-丘吉尔流域的WATROUTE路由模型相结合，可以制定径流情景。该路由模型在加拿大水文模型（CHARM）程序套件的路由组件WATROUTE中实现。此外，水路是水流模拟过程的计算瓶颈，导致运行时间长，特别是在预测未来许多年时。因此，找到显著减少WATROUTE运行时间的方法对马尼托巴水电公司至关重要。此外，路由模型的并行特性非常适合在图形处理单元（GPU）中固有的大规模并行处理器上执行，这些GPU最近已可用于通用科学计算。这项工作是对与马尼托巴水电合作的EngageGrant项目结果的扩展，其目的是创建一个高度并行、基于GPU、高性能计算的WATROUTE路由模型实现，以协助马尼托巴水电的资源规划过程。通过显著减少路由模型的运行时间，实现了这一目标的巨大进步。因此，该Engage Plus Grant的目的是追求使用GPU减少WATROUTE的整体运行时间，生产WATROUTE的发布就绪版本，探索WATROUTE对以前太大而无法处理的数据集的应用，并研究WATROUTE在具有多个GPU的系统上的使用。这项工作所实现的效益也可能对MEC-Surface and Hydrology System（MESH）和加拿大区域气候模式产生积极影响，因为两者都使用WATROUTE。