ABSTRACT: With the power, cooling, space, and performance restrictions facing large CPU-based systems, graphics processing units (GPUs) appear poised to become the next-generation super-computers. GPU-based systems already are two of the top ten fastest supercomputers on the Top500 list, with the potential to dominate this list in the future. While the hardware is highly scalable, achieving good parallel performance can be challenging. Language translation, code conversion and adaption, and performance optimization will be required. This presentation will survey existing efforts to use GPUs for weather and climate applications. Two general parallelization approaches will be discussed. The most common approach is to run select routines on the GPU but requires data transfers between CPU and GPU. Another approach is to run everything on the GPU and avoid the data transfers, but this can require significant effort to parallelize and optimize the code.
Robert Jacob (Chair) - Argonne National Laboratory