Minisymposium Presentation

The use of GPUs and accelerator architectures has become widespread in high-performance computing to achieve unprecedented throughput and computational model performance. The efficient usage of GPU architectures has long been envisioned at ECMWF, but it requires significant, often invasive code refactoring that can harm operational model performance on CPUs. In this talk we will describe the ongoing efforts at ECMWF to prepare the Integrated Forecasting System (IFS) for GPU accelerators through a combination of library development, data-structure refactoring and source-to-source translation. In close collaboration with ECMWF member states and supported by the Destination Earth initiative, we are aiming to restructure core model components of the IFS, and various technical infrastructure packages, to allow hybrid CPU-GPU execution. The focus is on sustainable solutions through modern software engineering methods that allow adaptation of the code to multiple architectures for continuous performance evaluation. We will report on the progress of the GPU adaptation of IFS via specific build modes of the IFS and provide an update on the adaptation of various sub-components. We will highlight specific code characteristics and subsequent challenges and present initial performance results to assess the potential performance gains on current and future architectures.