New High Performance GPGPU Code Transformation Framework Applied to Large Production Weather Prediction Code

Abstract

We introduce “Hybrid Fortran,” a new approach that allows a high-performance GPGPU port for structured grid Fortran codes. This technique only requires minimal changes for a CPU targeted codebase, which is a significant advancement in terms of productivity. It has been successfully applied to both dynamical core and physical processes of ASUCA, a Japanese mesoscale weather prediction model with more than 150k lines of code. By means of a minimal weather application that resembles ASUCA’s code structure, Hybrid Fortran is compared to both a performance model as well as today’s commonly used method, OpenACC. As a result, the Hybrid Fortran implementation is shown to deliver the same or better performance than OpenACC, and its performance agrees with the model both on CPU and GPU. In a full-scale production run, using an ASUCA grid with 1581 × 1301 × 58 cells and real-world weather data in 2km resolution, 24 NVIDIA Tesla P100 running the Hybrid Fortran–based GPU port are shown to replace more than fifty 18-core Intel Xeon Broadwell E5-2695 v4 running the reference implementation—an achievement comparable to more invasive GPGPU rewrites of other weather models.