An Integrated Approach to Porting Large Scientific Applications to GPUs

There are many large scientific applications that have been actively developed for several decades. However, in this time the hardware has evolved considerably. It is taking large scientific applications a very long time to get adjusted to the new computing infrastructure. This is because porting these applications to new hardware, such as Graphics Processing Units (GPUs), currently requires a huge amount of manual labor, even though the computations are very well suited for GPUs. In this paper we propose an integrated approach to semi-automatically port large long-lived scientific codes to GPUs. We propose a method that considerably reduces the effort required by experienced GPU programmers to port these applications. This approach is supported by a tool that is able to analyze, transform, and translate source code into different programming languages. We evaluate our approach by applying it to the Parallel Ocean Program, a representative, very large, and widely-used scientific application.