GPU Accelerated Surface Energy Balance Computations for Urban Environment Simulation

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Thursday, 8 January 2015: 11:00 AM
128AB (Phoenix Convention Center - West and North Buildings)
Matthew Overby, University of Minnesota, Duluth, MN; and P. Willemsen, E. Pardyjak, and R. Stoll

The urban microclimate plays an important role in determining local and large scale energy use. More specifically, the effects of urbanization on various climate-related aspects, such as the Urban Heat Island effect, need to be understood to better support sustainable urban developments. However, the complex interactions between the urban structure and the natural environment are not well understood, at least to the point where small scale energy effects within the urban space can be related to larger scale climate-related outcomes. The GEnUSiS project aims to better understand these relationships, focusing on simulating the surface energy balance across the urban domain using commodity graphics processing units (or GPUs) to accelerate the computations. GEnUSiS, or Green Environmental Urban Simulations for Sustainability, represents a highly interdisciplinary project aimed at generating knowledge to support more sustainable urban designs. The results from these efforts are designed to guide future urban projects, development, and policy.

Many challenges arise with solving small scale surface energy budgets across urban centers larger than a few blocks in size. The efficiency of computation quickly plays a role in determining the size and resolution of the urban spaces that can be simulated. Our surface energy budget computations utilize GPU-based resources to accelerate the calculations associated with radiation transport, turbulent advection, and land surface interactions. The computational framework is designed around the need to couple multiple models together into a heterogeneous computing substrate. Our system, called QUIC EnvSim, utilizes both CPU cores and GPU cores to handle these computations. In particular, we utilize NVIDIA's CUDA and OptiX frameworks to support the computations. For instance, with regard to radiation transport, our approach uses GPU-based ray tracing with NVIDIA's OptiX API to sample direct and diffuse shortwave irradiation, diffuse longwave irradiation, and longwave exchange between terrestrial objects. Simulated wavelengths have the potential to be absorbed, scattered, and reflected by objects in the domain, including participating media or vegetative volumes. Models implemented within the QUIC EnvSim framework are quite modular and can be linked with other surface energy budget components running on either the GPU or CPU.

In this work, we present the techniques and approaches we have developed to support GPU acceleration for solving the surface energy balance in urban domains. In particular, several optimizations and algorithm changes are necessary to afford efficient computation on the GPU. Moreover, QUIC EnvSim supports computation across multiple GPUs transparently by abstracting data buffer manipulation. Current results will also be presented demonstrating the capabilities of QUIC EnvSim and its ability to simulate the surface energy balance within urban domains.