Optimizing Total Energy–Mass Flux (TEMF) Planetary Boundary Layer Scheme for Intel’s Many Integrated Core (MIC) Architecture


In order to make use of the ever-improving microprocessor performance, the applications must be changed to take advantage of the parallelism of today's microprocessors. One such application that should be modernized is the weather research and forecasting (WRF) model, which is designed for numerical weather prediction and atmospheric research. The WRF software infrastructure consists of many elements like dynamic solvers and physics schemes. Numerical models are used to resolve the large-scale flow. However, subgrid-scale parameterizations are for an estimation of small-scale properties (e.g., boundary layer turbulence and convection, clouds, radiation). Those have a significant influence on the resolved scale due to the complex nonlinear nature of the atmosphere. For the cloudy planetary boundary layer (PBL), it is basic to parameterize vertical turbulent fluxes and subgrid-scale condensation in a very realistic manner. A parameterization primarily based on the whole energy-mass flux (TEMF) that unifies turbulence and moist convection parts produces a better result than other PBL schemes. Thus, we gift our optimization results for the TEMF PBL theme. Those optimizations included vectorization of the code to utilize multiple vector units inside each processor code. The optimizations improved the performance of the original TEMF code on Xeon Phi 7120P by a issue of 25.nine×. Furthermore, the same optimizations improved the performance of the TEMF on a twin socket configuration of eight-core Intel Xeon E5-2670 CPUs by a issue of eight.3× compared to the first TEMF code.

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