Reference number : GC-2017-Q1-00551, amendment number : , agreement type : G, recipient legal name : Henry, Christopher (The University of Winnipeg), recipient country : CA, recipient province : nan, recipient city : Manitoba, recipient postal code : nan, program name english : Engage Plus Grants for Universities, program name french : Subvention d'engagement partenarial Plus pour les universités, program purpose english : Manitoba Hydro's resource planning process is influenced by a variety of factors including water supply and_x000D_
electrical energy demand. As a result, understanding the sensitivity of planning decisions to future streamflow_x000D_
scenarios are important to their integrated resource planning process. Streamflow scenarios can be developed_x000D_
by combining global climate model simulated runoff values with the WATROUTE routing model for the_x000D_
Nelson-Churchill Watershed. The routing model is implemented in WATROUTE, the routing component of_x000D_
the Canadian Hydrological Model (CHARM) suite of programs. Further, WATROUTE is the computational_x000D_
bottleneck for the streamflow simulation processes, incurring long runtimes, especially when projecting many_x000D_
years into the future. Thus, finding ways of significantly reducing the runtime of WATROUTE is of great_x000D_
importance to Manitoba Hydro. Moreover, the parallel nature of the routing model is an ideal fit for execution_x000D_
on the massively parallel processors inherent in graphics processing units (GPUs), which have recently become_x000D_
available for general-purpose scientific computing. This work is an extension of the results from an Engage_x000D_
Grant with Manitoba Hydro, where the aim was to create a highly-parallel, GPU-based,_x000D_
high-performance-computing implementation of the WATROUTE routing model to assist Manitoba Hydro's_x000D_
resource planning process. Tremendous progress was achieved toward this aim through significant reduction in_x000D_
the routing model runtime. As a result, the aim of this Engage Plus Grant is to pursue the reduction of_x000D_
WATROUTE's overall runtime using GPUs, produce a release ready version of WATROUTE, explore the_x000D_
application of WATROUTE to datasets previously too large to process, and investigate the use of_x000D_
WATROUTE on systems with multiple GPUs. Benefits realized by this work may also have a positive impact_x000D_
on the MEC-Surface and Hydrology System (MESH) and the Canadian Regional Climate Model, as both use_x000D_
WATROUTE., program purpose french : Manitoba Hydro's resource planning process is influenced by a variety of factors including water supply and_x000D_
electrical energy demand. As a result, understanding the sensitivity of planning decisions to future streamflow_x000D_
scenarios are important to their integrated resource planning process. Streamflow scenarios can be developed_x000D_
by combining global climate model simulated runoff values with the WATROUTE routing model for the_x000D_
Nelson-Churchill Watershed. The routing model is implemented in WATROUTE, the routing component of_x000D_
the Canadian Hydrological Model (CHARM) suite of programs. Further, WATROUTE is the computational_x000D_
bottleneck for the streamflow simulation processes, incurring long runtimes, especially when projecting many_x000D_
years into the future. Thus, finding ways of significantly reducing the runtime of WATROUTE is of great_x000D_
importance to Manitoba Hydro. Moreover, the parallel nature of the routing model is an ideal fit for execution_x000D_
on the massively parallel processors inherent in graphics processing units (GPUs), which have recently become_x000D_
available for general-purpose scientific computing. This work is an extension of the results from an Engage_x000D_
Grant with Manitoba Hydro, where the aim was to create a highly-parallel, GPU-based,_x000D_
high-performance-computing implementation of the WATROUTE routing model to assist Manitoba Hydro's_x000D_
resource planning process. Tremendous progress was achieved toward this aim through significant reduction in_x000D_
the routing model runtime. As a result, the aim of this Engage Plus Grant is to pursue the reduction of_x000D_
WATROUTE's overall runtime using GPUs, produce a release ready version of WATROUTE, explore the_x000D_
application of WATROUTE to datasets previously too large to process, and investigate the use of_x000D_
WATROUTE on systems with multiple GPUs. Benefits realized by this work may also have a positive impact_x000D_
on the MEC-Surface and Hydrology System (MESH) and the Canadian Regional Climate Model, as both use_x000D_
WATROUTE., agreement title english : High performance computing framework for GCM-driven climate change simulation with the routing model WATROUTE, agreement title french : High performance computing framework for GCM-driven climate change simulation with the routing model WATROUTE, agreement number : EGP2, agreement value : 12500.0, agreement start date : 2017-05-10, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year. (2017-2018 to 2018-2019), additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2018-2019), owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada