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In this report we present a novel approach to model coupling forshared-memory multicore systems hosting OpenCL-compliant accelerators, which wecall The Glasgow Model Coupling Framework (GMCF). We discuss the implementationof a prototype of GMCF and its application to coupling the Weather Research andForecasting Model and an OpenCL-accelerated version of the Large Eddy Simulatorfor Urban Flows (LES) developed at DPRI.  The first stage of this work concerned the OpenCL port of the LES. Themethodology used for the OpenCL port is a combination of automated analysis andcode generation and rule-based manual parallelization. For the evaluation, thenon-OpenCL LES code was compiled using gfortran, fort and pgfortran}, in eachcase with auto-parallelization and auto-vectorization. The OpenCL-acceleratedversion of the LES achieves a 7 times speed-up on a NVIDIA GeForce GTX 480GPGPU, compared to the fastest possible compilation of the original coderunning on a 12-core Intel Xeon E5-2640.  In the second stage of this work, we built the Glasgow Model CouplingFramework and successfully used it to couple an OpenMP-parallelized WRFinstance with an OpenCL LES instance which runs the LES code on the GPGPI. Thesystem requires only very minimal changes to the original code. The reportdiscusses the rationale, aims, approach and implementation details of thiswork.

Model Coupling between the Weather Research and Forecasting Model and  the DPRI Large Eddy Simulator for Urban Flows on GPU-accelerated Multicore  Systems