Parallelized CCHE2D flow model with CUDA Fortran on Graphics Processing Units

• The Parallel Cyclic Reduction (PCR) method was used to parallelize the ADI solver.
• The parallelized SIP solver using Red–Black Checkerboard method was not stable.
• Allowing multiple equations solved at one thread resolved size limitation problem.
• CCHE2D implicit flow model was successfully parallelized using CUDA Fortran.
• Much higher computing efficiency and comparable accuracy was obtained on GPU.

This paper presents the CCHE2D implicit flow model parallelized using CUDA Fortran programming technique on Graphics Processing Units (GPUs). A parallelized implicit Alternating Direction Implicit (ADI) solver using Parallel Cyclic Reduction (PCR) algorithm on GPU is developed and tested. This solver outperforms the Strong Implicit Procedure (SIP) solver and its parallel alternatives. Computing accuracy and efficiency of both CPU and GPU versions of models were compared with one experimental case and one field case. It has been demonstrated that the parallelized CCHE2D flow model with CUDA Fortran is capable of accurately predicting steady flow or unsteady flow with a much higher computing efficiency on the GPU.